Complex and extensive post-transcriptional regulation revealed by integrative proteomic and transcriptomic analysis of metabolite stress response in Clostridium acetobutylicum.

PubMed

Venkataramanan, Keerthi P; Min, Lie; Hou, Shuyu; Jones, Shawn W; Ralston, Matthew T; Lee, Kelvin H; Papoutsakis, E Terry

2015-01-01

Clostridium acetobutylicum is a model organism for both clostridial biology and solvent production. The organism is exposed to its own toxic metabolites butyrate and butanol, which trigger an adaptive stress response. Integrative analysis of proteomic and RNAseq data may provide novel insights into post-transcriptional regulation. The identified iTRAQ-based quantitative stress proteome is made up of 616 proteins with a 15 % genome coverage. The differentially expressed proteome correlated poorly with the corresponding differential RNAseq transcriptome. Up to 31 % of the differentially expressed proteins under stress displayed patterns opposite to those of the transcriptome, thus suggesting significant post-transcriptional regulation. The differential proteome of the translation machinery suggests that cells employ a different subset of ribosomal proteins under stress. Several highly upregulated proteins but with low mRNA levels possessed mRNAs with long 5'UTRs and strong RBS scores, thus supporting the argument that regulatory elements on the long 5'UTRs control their translation. For example, the oxidative stress response rubrerythrin was upregulated only at the protein level up to 40-fold without significant mRNA changes. We also identified many leaderless transcripts, several displaying different transcriptional start sites, thus suggesting mRNA-trimming mechanisms under stress. Downregulation of Rho and partner proteins pointed to changes in transcriptional elongation and termination under stress. The integrative proteomic-transcriptomic analysis demonstrated complex expression patterns of a large fraction of the proteome. Such patterns could not have been detected with one or the other omic analyses. Our analysis proposes the involvement of specific molecular mechanisms of post-transcriptional regulation to explain the observed complex stress response.

Integrative omics analysis. A study based on Plasmodium falciparum mRNA and protein data.

PubMed

Tomescu, Oana A; Mattanovich, Diethard; Thallinger, Gerhard G

2014-01-01

Technological improvements have shifted the focus from data generation to data analysis. The availability of large amounts of data from transcriptomics, protemics and metabolomics experiments raise new questions concerning suitable integrative analysis methods. We compare three integrative analysis techniques (co-inertia analysis, generalized singular value decomposition and integrative biclustering) by applying them to gene and protein abundance data from the six life cycle stages of Plasmodium falciparum. Co-inertia analysis is an analysis method used to visualize and explore gene and protein data. The generalized singular value decomposition has shown its potential in the analysis of two transcriptome data sets. Integrative Biclustering applies biclustering to gene and protein data. Using CIA, we visualize the six life cycle stages of Plasmodium falciparum, as well as GO terms in a 2D plane and interpret the spatial configuration. With GSVD, we decompose the transcriptomic and proteomic data sets into matrices with biologically meaningful interpretations and explore the processes captured by the data sets. IBC identifies groups of genes, proteins, GO Terms and life cycle stages of Plasmodium falciparum. We show method-specific results as well as a network view of the life cycle stages based on the results common to all three methods. Additionally, by combining the results of the three methods, we create a three-fold validated network of life cycle stage specific GO terms: Sporozoites are associated with transcription and transport; merozoites with entry into host cell as well as biosynthetic and metabolic processes; rings with oxidation-reduction processes; trophozoites with glycolysis and energy production; schizonts with antigenic variation and immune response; gametocyctes with DNA packaging and mitochondrial transport. Furthermore, the network connectivity underlines the separation of the intraerythrocytic cycle from the gametocyte and sporozoite stages. Using integrative analysis techniques, we can integrate knowledge from different levels and obtain a wider view of the system under study. The overlap between method-specific and common results is considerable, even if the basic mathematical assumptions are very different. The three-fold validated network of life cycle stage characteristics of Plasmodium falciparum could identify a large amount of the known associations from literature in only one study.

Integrative omics analysis. A study based on Plasmodium falciparum mRNA and protein data

PubMed Central

2014-01-01

Background Technological improvements have shifted the focus from data generation to data analysis. The availability of large amounts of data from transcriptomics, protemics and metabolomics experiments raise new questions concerning suitable integrative analysis methods. We compare three integrative analysis techniques (co-inertia analysis, generalized singular value decomposition and integrative biclustering) by applying them to gene and protein abundance data from the six life cycle stages of Plasmodium falciparum. Co-inertia analysis is an analysis method used to visualize and explore gene and protein data. The generalized singular value decomposition has shown its potential in the analysis of two transcriptome data sets. Integrative Biclustering applies biclustering to gene and protein data. Results Using CIA, we visualize the six life cycle stages of Plasmodium falciparum, as well as GO terms in a 2D plane and interpret the spatial configuration. With GSVD, we decompose the transcriptomic and proteomic data sets into matrices with biologically meaningful interpretations and explore the processes captured by the data sets. IBC identifies groups of genes, proteins, GO Terms and life cycle stages of Plasmodium falciparum. We show method-specific results as well as a network view of the life cycle stages based on the results common to all three methods. Additionally, by combining the results of the three methods, we create a three-fold validated network of life cycle stage specific GO terms: Sporozoites are associated with transcription and transport; merozoites with entry into host cell as well as biosynthetic and metabolic processes; rings with oxidation-reduction processes; trophozoites with glycolysis and energy production; schizonts with antigenic variation and immune response; gametocyctes with DNA packaging and mitochondrial transport. Furthermore, the network connectivity underlines the separation of the intraerythrocytic cycle from the gametocyte and sporozoite stages. Conclusion Using integrative analysis techniques, we can integrate knowledge from different levels and obtain a wider view of the system under study. The overlap between method-specific and common results is considerable, even if the basic mathematical assumptions are very different. The three-fold validated network of life cycle stage characteristics of Plasmodium falciparum could identify a large amount of the known associations from literature in only one study. PMID:25033389

Extraction of Molecular Features through Exome to Transcriptome Alignment

PubMed Central

Mudvari, Prakriti; Kowsari, Kamran; Cole, Charles; Mazumder, Raja; Horvath, Anelia

2014-01-01

Integrative Next Generation Sequencing (NGS) DNA and RNA analyses have very recently become feasible, and the published to date studies have discovered critical disease implicated pathways, and diagnostic and therapeutic targets. A growing number of exomes, genomes and transcriptomes from the same individual are quickly accumulating, providing unique venues for mechanistic and regulatory features analysis, and, at the same time, requiring new exploration strategies. In this study, we have integrated variation and expression information of four NGS datasets from the same individual: normal and tumor breast exomes and transcriptomes. Focusing on SNPcentered variant allelic prevalence, we illustrate analytical algorithms that can be applied to extract or validate potential regulatory elements, such as expression or growth advantage, imprinting, loss of heterozygosity (LOH), somatic changes, and RNA editing. In addition, we point to some critical elements that might bias the output and recommend alternative measures to maximize the confidence of findings. The need for such strategies is especially recognized within the growing appreciation of the concept of systems biology: integrative exploration of genome and transcriptome features reveal mechanistic and regulatory insights that reach far beyond linear addition of the individual datasets. PMID:24791251

Transcriptome analysis of Brassica napus pod using RNA-Seq and identification of lipid-related candidate genes.

PubMed

Xu, Hai-Ming; Kong, Xiang-Dong; Chen, Fei; Huang, Ji-Xiang; Lou, Xiang-Yang; Zhao, Jian-Yi

2015-10-24

Brassica napus is an important oilseed crop. Dissection of the genetic architecture underlying oil-related biological processes will greatly facilitates the genetic improvement of rapeseed. The differential gene expression during pod development offers a snapshot on the genes responsible for oil accumulation in. To identify candidate genes in the linkage peaks reported previously, we used RNA sequencing (RNA-Seq) technology to analyze the pod transcriptomes of German cultivar Sollux and Chinese inbred line Gaoyou. The RNA samples were collected for RNA-Seq at 5-7, 15-17 and 25-27 days after flowering (DAF). Bioinformatics analysis was performed to investigate differentially expressed genes (DEGs). Gene annotation analysis was integrated with QTL mapping and Brassica napus pod transcriptome profiling to detect potential candidate genes in oilseed. Four hundred sixty five and two thousand, one hundred fourteen candidate DEGs were identified, respectively, between two varieties at the same stages and across different periods of each variety. Then, 33 DEGs between Sollux and Gaoyou were identified as the candidate genes affecting seed oil content by combining those DEGs with the quantitative trait locus (QTL) mapping results, of which, one was found to be homologous to Arabidopsis thaliana lipid-related genes. Intervarietal DEGs of lipid pathways in QTL regions represent important candidate genes for oil-related traits. Integrated analysis of transcriptome profiling, QTL mapping and comparative genomics with other relative species leads to efficient identification of most plausible functional genes underlying oil-content related characters, offering valuable resources for bettering breeding program of Brassica napus. This study provided a comprehensive overview on the pod transcriptomes of two varieties with different oil-contents at the three developmental stages.

De novo Assembly and Analysis of the Chilean Pencil Catfish Trichomycterus areolatus Transcriptome

PubMed Central

Schulze, Thomas T.; Ali, Jonathan M.; Bartlett, Maggie L.; McFarland, Madalyn M.; Clement, Emalie J.; Won, Harim I.; Sanford, Austin G.; Monzingo, Elyssa B.; Martens, Matthew C.; Hemsley, Ryan M.; Kumar, Sidharta; Gouin, Nicolas; Kolok, Alan S.; Davis, Paul H.

2016-01-01

Trichomycterus areolatus is an endemic species of pencil catfish that inhabits the riffles and rapids of many freshwater ecosystems of Chile. Despite its unique adaptation to Chile's high gradient watersheds and therefore potential application in the investigation of ecosystem integrity and environmental contamination, relatively little is known regarding the molecular biology of this environmental sentinel. Here, we detail the assembly of the Trichomycterus areolatus transcriptome, a molecular resource for the study of this organism and its molecular response to the environment. RNA-Seq reads were obtained by next-generation sequencing with an Illumina® platform and processed using PRINSEQ. The transcriptome assembly was performed using TRINITY assembler. Transcriptome validation was performed by functional characterization with KOG, KEGG, and GO analyses. Additionally, differential expression analysis highlights sex-specific expression patterns, and a list of endocrine and oxidative stress related transcripts are included. PMID:27672404

From proteomics to systems biology: MAPA, MASS WESTERN, PROMEX, and COVAIN as a user-oriented platform.

PubMed

Weckwerth, Wolfram; Wienkoop, Stefanie; Hoehenwarter, Wolfgang; Egelhofer, Volker; Sun, Xiaoliang

2014-01-01

Genome sequencing and systems biology are revolutionizing life sciences. Proteomics emerged as a fundamental technique of this novel research area as it is the basis for gene function analysis and modeling of dynamic protein networks. Here a complete proteomics platform suited for functional genomics and systems biology is presented. The strategy includes MAPA (mass accuracy precursor alignment; http://www.univie.ac.at/mosys/software.html ) as a rapid exploratory analysis step; MASS WESTERN for targeted proteomics; COVAIN ( http://www.univie.ac.at/mosys/software.html ) for multivariate statistical analysis, data integration, and data mining; and PROMEX ( http://www.univie.ac.at/mosys/databases.html ) as a database module for proteogenomics and proteotypic peptides for targeted analysis. Moreover, the presented platform can also be utilized to integrate metabolomics and transcriptomics data for the analysis of metabolite-protein-transcript correlations and time course analysis using COVAIN. Examples for the integration of MAPA and MASS WESTERN data, proteogenomic and metabolic modeling approaches for functional genomics, phosphoproteomics by integration of MOAC (metal-oxide affinity chromatography) with MAPA, and the integration of metabolomics, transcriptomics, proteomics, and physiological data using this platform are presented. All software and step-by-step tutorials for data processing and data mining can be downloaded from http://www.univie.ac.at/mosys/software.html.

Integrated mRNA and miRNA transcriptome reveal a cross-talk between developing response and hormone signaling for the seed kernels of Siberian apricot

PubMed Central

Niu, Jun; Wang, Jia; An, Jiyong; Liu, Lili; Lin, Zixin; Wang, Rui; Wang, Libing; Ma, Chao; Shi, Lingling; Lin, Shanzhi

2016-01-01

Recently, our transcriptomic analysis has identified some functional genes responsible for oil biosynthesis in developing SASK, yet miRNA-mediated regulation for SASK development and oil accumulation is poorly understood. Here, 3 representative periods of 10, 30 and 60 DAF were selected for sRNA sequencing based on the dynamic patterns of growth tendency and oil content of developing SASK. By miRNA transcriptomic analysis, we characterized 296 known and 44 novel miRNAs in developing SASK, among which 36 known and 6 novel miRNAs respond specifically to developing SASK. Importantly, we performed an integrated analysis of mRNA and miRNA transcriptome as well as qRT-PCR detection to identify some key miRNAs and their targets (miR156-SPL, miR160-ARF18, miR164-NAC1, miR171h-SCL6, miR172-AP2, miR395-AUX22B, miR530-P2C37, miR393h-TIR1/AFB2 and psi-miRn5-SnRK2A) potentially involved in developing response and hormone signaling of SASK. Our results provide new insights into the important regulatory function of cross-talk between development response and hormone signaling for SASK oil accumulation. PMID:27762296

Integrated mRNA and miRNA transcriptome reveal a cross-talk between developing response and hormone signaling for the seed kernels of Siberian apricot.

PubMed

Niu, Jun; Wang, Jia; An, Jiyong; Liu, Lili; Lin, Zixin; Wang, Rui; Wang, Libing; Ma, Chao; Shi, Lingling; Lin, Shanzhi

2016-10-20

Recently, our transcriptomic analysis has identified some functional genes responsible for oil biosynthesis in developing SASK, yet miRNA-mediated regulation for SASK development and oil accumulation is poorly understood. Here, 3 representative periods of 10, 30 and 60 DAF were selected for sRNA sequencing based on the dynamic patterns of growth tendency and oil content of developing SASK. By miRNA transcriptomic analysis, we characterized 296 known and 44 novel miRNAs in developing SASK, among which 36 known and 6 novel miRNAs respond specifically to developing SASK. Importantly, we performed an integrated analysis of mRNA and miRNA transcriptome as well as qRT-PCR detection to identify some key miRNAs and their targets (miR156-SPL, miR160-ARF18, miR164-NAC1, miR171h-SCL6, miR172-AP2, miR395-AUX22B, miR530-P2C37, miR393h-TIR1/AFB2 and psi-miRn5-SnRK2A) potentially involved in developing response and hormone signaling of SASK. Our results provide new insights into the important regulatory function of cross-talk between development response and hormone signaling for SASK oil accumulation.

SIDR: simultaneous isolation and parallel sequencing of genomic DNA and total RNA from single cells.

PubMed

Han, Kyung Yeon; Kim, Kyu-Tae; Joung, Je-Gun; Son, Dae-Soon; Kim, Yeon Jeong; Jo, Areum; Jeon, Hyo-Jeong; Moon, Hui-Sung; Yoo, Chang Eun; Chung, Woosung; Eum, Hye Hyeon; Kim, Sangmin; Kim, Hong Kwan; Lee, Jeong Eon; Ahn, Myung-Ju; Lee, Hae-Ock; Park, Donghyun; Park, Woong-Yang

2018-01-01

Simultaneous sequencing of the genome and transcriptome at the single-cell level is a powerful tool for characterizing genomic and transcriptomic variation and revealing correlative relationships. However, it remains technically challenging to analyze both the genome and transcriptome in the same cell. Here, we report a novel method for simultaneous isolation of genomic DNA and total RNA (SIDR) from single cells, achieving high recovery rates with minimal cross-contamination, as is crucial for accurate description and integration of the single-cell genome and transcriptome. For reliable and efficient separation of genomic DNA and total RNA from single cells, the method uses hypotonic lysis to preserve nuclear lamina integrity and subsequently captures the cell lysate using antibody-conjugated magnetic microbeads. Evaluating the performance of this method using real-time PCR demonstrated that it efficiently recovered genomic DNA and total RNA. Thorough data quality assessments showed that DNA and RNA simultaneously fractionated by the SIDR method were suitable for genome and transcriptome sequencing analysis at the single-cell level. The integration of single-cell genome and transcriptome sequencing by SIDR (SIDR-seq) showed that genetic alterations, such as copy-number and single-nucleotide variations, were more accurately captured by single-cell SIDR-seq compared with conventional single-cell RNA-seq, although copy-number variations positively correlated with the corresponding gene expression levels. These results suggest that SIDR-seq is potentially a powerful tool to reveal genetic heterogeneity and phenotypic information inferred from gene expression patterns at the single-cell level. © 2018 Han et al.; Published by Cold Spring Harbor Laboratory Press.

SIDR: simultaneous isolation and parallel sequencing of genomic DNA and total RNA from single cells

PubMed Central

Han, Kyung Yeon; Kim, Kyu-Tae; Joung, Je-Gun; Son, Dae-Soon; Kim, Yeon Jeong; Jo, Areum; Jeon, Hyo-Jeong; Moon, Hui-Sung; Yoo, Chang Eun; Chung, Woosung; Eum, Hye Hyeon; Kim, Sangmin; Kim, Hong Kwan; Lee, Jeong Eon; Ahn, Myung-Ju; Lee, Hae-Ock; Park, Donghyun; Park, Woong-Yang

2018-01-01

Simultaneous sequencing of the genome and transcriptome at the single-cell level is a powerful tool for characterizing genomic and transcriptomic variation and revealing correlative relationships. However, it remains technically challenging to analyze both the genome and transcriptome in the same cell. Here, we report a novel method for simultaneous isolation of genomic DNA and total RNA (SIDR) from single cells, achieving high recovery rates with minimal cross-contamination, as is crucial for accurate description and integration of the single-cell genome and transcriptome. For reliable and efficient separation of genomic DNA and total RNA from single cells, the method uses hypotonic lysis to preserve nuclear lamina integrity and subsequently captures the cell lysate using antibody-conjugated magnetic microbeads. Evaluating the performance of this method using real-time PCR demonstrated that it efficiently recovered genomic DNA and total RNA. Thorough data quality assessments showed that DNA and RNA simultaneously fractionated by the SIDR method were suitable for genome and transcriptome sequencing analysis at the single-cell level. The integration of single-cell genome and transcriptome sequencing by SIDR (SIDR-seq) showed that genetic alterations, such as copy-number and single-nucleotide variations, were more accurately captured by single-cell SIDR-seq compared with conventional single-cell RNA-seq, although copy-number variations positively correlated with the corresponding gene expression levels. These results suggest that SIDR-seq is potentially a powerful tool to reveal genetic heterogeneity and phenotypic information inferred from gene expression patterns at the single-cell level. PMID:29208629

An integrative systems genetics approach reveals potential causal genes and pathways related to obesity.

PubMed

Kogelman, Lisette J A; Zhernakova, Daria V; Westra, Harm-Jan; Cirera, Susanna; Fredholm, Merete; Franke, Lude; Kadarmideen, Haja N

2015-10-20

Obesity is a multi-factorial health problem in which genetic factors play an important role. Limited results have been obtained in single-gene studies using either genomic or transcriptomic data. RNA sequencing technology has shown its potential in gaining accurate knowledge about the transcriptome, and may reveal novel genes affecting complex diseases. Integration of genomic and transcriptomic variation (expression quantitative trait loci [eQTL] mapping) has identified causal variants that affect complex diseases. We integrated transcriptomic data from adipose tissue and genomic data from a porcine model to investigate the mechanisms involved in obesity using a systems genetics approach. Using a selective gene expression profiling approach, we selected 36 animals based on a previously created genomic Obesity Index for RNA sequencing of subcutaneous adipose tissue. Differential expression analysis was performed using the Obesity Index as a continuous variable in a linear model. eQTL mapping was then performed to integrate 60 K porcine SNP chip data with the RNA sequencing data. Results were restricted based on genome-wide significant single nucleotide polymorphisms, detected differentially expressed genes, and previously detected co-expressed gene modules. Further data integration was performed by detecting co-expression patterns among eQTLs and integration with protein data. Differential expression analysis of RNA sequencing data revealed 458 differentially expressed genes. The eQTL mapping resulted in 987 cis-eQTLs and 73 trans-eQTLs (false discovery rate < 0.05), of which the cis-eQTLs were associated with metabolic pathways. We reduced the eQTL search space by focusing on differentially expressed and co-expressed genes and disease-associated single nucleotide polymorphisms to detect obesity-related genes and pathways. Building a co-expression network using eQTLs resulted in the detection of a module strongly associated with lipid pathways. Furthermore, we detected several obesity candidate genes, for example, ENPP1, CTSL, and ABHD12B. To our knowledge, this is the first study to perform an integrated genomics and transcriptomics (eQTL) study using, and modeling, genomic and subcutaneous adipose tissue RNA sequencing data on obesity in a porcine model. We detected several pathways and potential causal genes for obesity. Further validation and investigation may reveal their exact function and association with obesity.

VESPA: software to facilitate genomic annotation of prokaryotic organisms through integration of proteomic and transcriptomic data.

PubMed

Peterson, Elena S; McCue, Lee Ann; Schrimpe-Rutledge, Alexandra C; Jensen, Jeffrey L; Walker, Hyunjoo; Kobold, Markus A; Webb, Samantha R; Payne, Samuel H; Ansong, Charles; Adkins, Joshua N; Cannon, William R; Webb-Robertson, Bobbie-Jo M

2012-04-05

The procedural aspects of genome sequencing and assembly have become relatively inexpensive, yet the full, accurate structural annotation of these genomes remains a challenge. Next-generation sequencing transcriptomics (RNA-Seq), global microarrays, and tandem mass spectrometry (MS/MS)-based proteomics have demonstrated immense value to genome curators as individual sources of information, however, integrating these data types to validate and improve structural annotation remains a major challenge. Current visual and statistical analytic tools are focused on a single data type, or existing software tools are retrofitted to analyze new data forms. We present Visual Exploration and Statistics to Promote Annotation (VESPA) is a new interactive visual analysis software tool focused on assisting scientists with the annotation of prokaryotic genomes though the integration of proteomics and transcriptomics data with current genome location coordinates. VESPA is a desktop Java™ application that integrates high-throughput proteomics data (peptide-centric) and transcriptomics (probe or RNA-Seq) data into a genomic context, all of which can be visualized at three levels of genomic resolution. Data is interrogated via searches linked to the genome visualizations to find regions with high likelihood of mis-annotation. Search results are linked to exports for further validation outside of VESPA or potential coding-regions can be analyzed concurrently with the software through interaction with BLAST. VESPA is demonstrated on two use cases (Yersinia pestis Pestoides F and Synechococcus sp. PCC 7002) to demonstrate the rapid manner in which mis-annotations can be found and explored in VESPA using either proteomics data alone, or in combination with transcriptomic data. VESPA is an interactive visual analytics tool that integrates high-throughput data into a genomic context to facilitate the discovery of structural mis-annotations in prokaryotic genomes. Data is evaluated via visual analysis across multiple levels of genomic resolution, linked searches and interaction with existing bioinformatics tools. We highlight the novel functionality of VESPA and core programming requirements for visualization of these large heterogeneous datasets for a client-side application. The software is freely available at https://www.biopilot.org/docs/Software/Vespa.php.

VESPA: software to facilitate genomic annotation of prokaryotic organisms through integration of proteomic and transcriptomic data

PubMed Central

2012-01-01

Background The procedural aspects of genome sequencing and assembly have become relatively inexpensive, yet the full, accurate structural annotation of these genomes remains a challenge. Next-generation sequencing transcriptomics (RNA-Seq), global microarrays, and tandem mass spectrometry (MS/MS)-based proteomics have demonstrated immense value to genome curators as individual sources of information, however, integrating these data types to validate and improve structural annotation remains a major challenge. Current visual and statistical analytic tools are focused on a single data type, or existing software tools are retrofitted to analyze new data forms. We present Visual Exploration and Statistics to Promote Annotation (VESPA) is a new interactive visual analysis software tool focused on assisting scientists with the annotation of prokaryotic genomes though the integration of proteomics and transcriptomics data with current genome location coordinates. Results VESPA is a desktop Java™ application that integrates high-throughput proteomics data (peptide-centric) and transcriptomics (probe or RNA-Seq) data into a genomic context, all of which can be visualized at three levels of genomic resolution. Data is interrogated via searches linked to the genome visualizations to find regions with high likelihood of mis-annotation. Search results are linked to exports for further validation outside of VESPA or potential coding-regions can be analyzed concurrently with the software through interaction with BLAST. VESPA is demonstrated on two use cases (Yersinia pestis Pestoides F and Synechococcus sp. PCC 7002) to demonstrate the rapid manner in which mis-annotations can be found and explored in VESPA using either proteomics data alone, or in combination with transcriptomic data. Conclusions VESPA is an interactive visual analytics tool that integrates high-throughput data into a genomic context to facilitate the discovery of structural mis-annotations in prokaryotic genomes. Data is evaluated via visual analysis across multiple levels of genomic resolution, linked searches and interaction with existing bioinformatics tools. We highlight the novel functionality of VESPA and core programming requirements for visualization of these large heterogeneous datasets for a client-side application. The software is freely available at https://www.biopilot.org/docs/Software/Vespa.php. PMID:22480257

Customized workflow development and data modularization concepts for RNA-Sequencing and metatranscriptome experiments.

PubMed

Lott, Steffen C; Wolfien, Markus; Riege, Konstantin; Bagnacani, Andrea; Wolkenhauer, Olaf; Hoffmann, Steve; Hess, Wolfgang R

2017-11-10

RNA-Sequencing (RNA-Seq) has become a widely used approach to study quantitative and qualitative aspects of transcriptome data. The variety of RNA-Seq protocols, experimental study designs and the characteristic properties of the organisms under investigation greatly affect downstream and comparative analyses. In this review, we aim to explain the impact of structured pre-selection, classification and integration of best-performing tools within modularized data analysis workflows and ready-to-use computing infrastructures towards experimental data analyses. We highlight examples for workflows and use cases that are presented for pro-, eukaryotic and mixed dual RNA-Seq (meta-transcriptomics) experiments. In addition, we are summarizing the expertise of the laboratories participating in the project consortium "Structured Analysis and Integration of RNA-Seq experiments" (de.STAIR) and its integration with the Galaxy-workbench of the RNA Bioinformatics Center (RBC). Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

A practical data processing workflow for multi-OMICS projects.

PubMed

Kohl, Michael; Megger, Dominik A; Trippler, Martin; Meckel, Hagen; Ahrens, Maike; Bracht, Thilo; Weber, Frank; Hoffmann, Andreas-Claudius; Baba, Hideo A; Sitek, Barbara; Schlaak, Jörg F; Meyer, Helmut E; Stephan, Christian; Eisenacher, Martin

2014-01-01

Multi-OMICS approaches aim on the integration of quantitative data obtained for different biological molecules in order to understand their interrelation and the functioning of larger systems. This paper deals with several data integration and data processing issues that frequently occur within this context. To this end, the data processing workflow within the PROFILE project is presented, a multi-OMICS project that aims on identification of novel biomarkers and the development of new therapeutic targets for seven important liver diseases. Furthermore, a software called CrossPlatformCommander is sketched, which facilitates several steps of the proposed workflow in a semi-automatic manner. Application of the software is presented for the detection of novel biomarkers, their ranking and annotation with existing knowledge using the example of corresponding Transcriptomics and Proteomics data sets obtained from patients suffering from hepatocellular carcinoma. Additionally, a linear regression analysis of Transcriptomics vs. Proteomics data is presented and its performance assessed. It was shown, that for capturing profound relations between Transcriptomics and Proteomics data, a simple linear regression analysis is not sufficient and implementation and evaluation of alternative statistical approaches are needed. Additionally, the integration of multivariate variable selection and classification approaches is intended for further development of the software. Although this paper focuses only on the combination of data obtained from quantitative Proteomics and Transcriptomics experiments, several approaches and data integration steps are also applicable for other OMICS technologies. Keeping specific restrictions in mind the suggested workflow (or at least parts of it) may be used as a template for similar projects that make use of different high throughput techniques. This article is part of a Special Issue entitled: Computational Proteomics in the Post-Identification Era. Guest Editors: Martin Eisenacher and Christian Stephan. Copyright © 2013 Elsevier B.V. All rights reserved.

Identifier mapping performance for integrating transcriptomics and proteomics experimental results

PubMed Central

2011-01-01

Background Studies integrating transcriptomic data with proteomic data can illuminate the proteome more clearly than either separately. Integromic studies can deepen understanding of the dynamic complex regulatory relationship between the transcriptome and the proteome. Integrating these data dictates a reliable mapping between the identifier nomenclature resultant from the two high-throughput platforms. However, this kind of analysis is well known to be hampered by lack of standardization of identifier nomenclature among proteins, genes, and microarray probe sets. Therefore data integration may also play a role in critiquing the fallible gene identifications that both platforms emit. Results We compared three freely available internet-based identifier mapping resources for mapping UniProt accessions (ACCs) to Affymetrix probesets identifications (IDs): DAVID, EnVision, and NetAffx. Liquid chromatography-tandem mass spectrometry analyses of 91 endometrial cancer and 7 noncancer samples generated 11,879 distinct ACCs. For each ACC, we compared the retrieval sets of probeset IDs from each mapping resource. We confirmed a high level of discrepancy among the mapping resources. On the same samples, mRNA expression was available. Therefore, to evaluate the quality of each ACC-to-probeset match, we calculated proteome-transcriptome correlations, and compared the resources presuming that better mapping of identifiers should generate a higher proportion of mapped pairs with strong inter-platform correlations. A mixture model for the correlations fitted well and supported regression analysis, providing a window into the performance of the mapping resources. The resources have added and dropped matches over two years, but their overall performance has not changed. Conclusions The methods presented here serve to achieve concrete context-specific insight, to support well-informed decisions in choosing an ID mapping strategy for "omic" data merging. PMID:21619611

Comparative whole genome transcriptome and metabolome analyses of five Klebsiella pneumonia strains.

PubMed

Lee, Soojin; Kim, Borim; Yang, Jeongmo; Jeong, Daun; Park, Soohyun; Shin, Sang Heum; Kook, Jun Ho; Yang, Kap-Seok; Lee, Jinwon

2015-11-01

The integration of transcriptomics and metabolomics can provide precise information on gene-to-metabolite networks for identifying the function of novel genes. The goal of this study was to identify novel gene functions involved in 2,3-butanediol (2,3-BDO) biosynthesis by a comprehensive analysis of the transcriptome and metabolome of five mutated Klebsiella pneumonia strains (∆wabG = SGSB100, ∆wabG∆budA = SGSB106, ∆wabG∆budB = SGSB107, ∆wabG∆budC = SGSB108, ∆wabG∆budABC = SGSB109). First, the transcriptomes of all five mutants were analyzed and the genes exhibiting reproducible changes in expression were determined. The transcriptome was well conserved among the five strains, and differences in gene expression occurred mainly in genes coding for 2,3-BDO biosynthesis (budA, budB, and budC) and the genes involved in the degradation of reactive oxygen, biosynthesis and transport of arginine, cysteine biosynthesis, sulfur metabolism, oxidoreductase reaction, and formate dehydrogenase reaction. Second, differences in the metabolome (estimated by carbon distribution, CO2 emission, and redox balance) among the five mutant strains due to gene alteration of the 2,3-BDO operon were detected. The functional genomics approach integrating metabolomics and transcriptomics in K. Pneumonia presented here provides an innovative means of identifying novel gene functions involved in 2,3-BDO biosynthesis metabolism and whole cell metabolism.

Integrative structural annotation of de novo RNA-Seq provides an accurate reference gene set of the enormous genome of the onion (Allium cepa L.)

PubMed Central

Kim, Seungill; Kim, Myung-Shin; Kim, Yong-Min; Yeom, Seon-In; Cheong, Kyeongchae; Kim, Ki-Tae; Jeon, Jongbum; Kim, Sunggil; Kim, Do-Sun; Sohn, Seong-Han; Lee, Yong-Hwan; Choi, Doil

2015-01-01

The onion (Allium cepa L.) is one of the most widely cultivated and consumed vegetable crops in the world. Although a considerable amount of onion transcriptome data has been deposited into public databases, the sequences of the protein-coding genes are not accurate enough to be used, owing to non-coding sequences intermixed with the coding sequences. We generated a high-quality, annotated onion transcriptome from de novo sequence assembly and intensive structural annotation using the integrated structural gene annotation pipeline (ISGAP), which identified 54,165 protein-coding genes among 165,179 assembled transcripts totalling 203.0 Mb by eliminating the intron sequences. ISGAP performed reliable annotation, recognizing accurate gene structures based on reference proteins, and ab initio gene models of the assembled transcripts. Integrative functional annotation and gene-based SNP analysis revealed a whole biological repertoire of genes and transcriptomic variation in the onion. The method developed in this study provides a powerful tool for the construction of reference gene sets for organisms based solely on de novo transcriptome data. Furthermore, the reference genes and their variation described here for the onion represent essential tools for molecular breeding and gene cloning in Allium spp. PMID:25362073

Integrated analysis of whole-exome sequencing and transcriptome profiling in males with autism spectrum disorders.

PubMed

Codina-Solà, Marta; Rodríguez-Santiago, Benjamín; Homs, Aïda; Santoyo, Javier; Rigau, Maria; Aznar-Laín, Gemma; Del Campo, Miguel; Gener, Blanca; Gabau, Elisabeth; Botella, María Pilar; Gutiérrez-Arumí, Armand; Antiñolo, Guillermo; Pérez-Jurado, Luis Alberto; Cuscó, Ivon

2015-01-01

Autism spectrum disorders (ASD) are a group of neurodevelopmental disorders with high heritability. Recent findings support a highly heterogeneous and complex genetic etiology including rare de novo and inherited mutations or chromosomal rearrangements as well as double or multiple hits. We performed whole-exome sequencing (WES) and blood cell transcriptome by RNAseq in a subset of male patients with idiopathic ASD (n = 36) in order to identify causative genes, transcriptomic alterations, and susceptibility variants. We detected likely monogenic causes in seven cases: five de novo (SCN2A, MED13L, KCNV1, CUL3, and PTEN) and two inherited X-linked variants (MAOA and CDKL5). Transcriptomic analyses allowed the identification of intronic causative mutations missed by the usual filtering of WES and revealed functional consequences of some rare mutations. These included aberrant transcripts (PTEN, POLR3C), deregulated expression in 1.7% of mutated genes (that is, SEMA6B, MECP2, ANK3, CREBBP), allele-specific expression (FUS, MTOR, TAF1C), and non-sense-mediated decay (RIT1, ALG9). The analysis of rare inherited variants showed enrichment in relevant pathways such as the PI3K-Akt signaling and the axon guidance. Integrative analysis of WES and blood RNAseq data has proven to be an efficient strategy to identify likely monogenic forms of ASD (19% in our cohort), as well as additional rare inherited mutations that can contribute to ASD risk in a multifactorial manner. Blood transcriptomic data, besides validating 88% of expressed variants, allowed the identification of missed intronic mutations and revealed functional correlations of genetic variants, including changes in splicing, expression levels, and allelic expression.

The Human Blood Metabolome-Transcriptome Interface

PubMed Central

Schramm, Katharina; Adamski, Jerzy; Gieger, Christian; Herder, Christian; Carstensen, Maren; Peters, Annette; Rathmann, Wolfgang; Roden, Michael; Strauch, Konstantin; Suhre, Karsten; Kastenmüller, Gabi; Prokisch, Holger; Theis, Fabian J.

2015-01-01

Biological systems consist of multiple organizational levels all densely interacting with each other to ensure function and flexibility of the system. Simultaneous analysis of cross-sectional multi-omics data from large population studies is a powerful tool to comprehensively characterize the underlying molecular mechanisms on a physiological scale. In this study, we systematically analyzed the relationship between fasting serum metabolomics and whole blood transcriptomics data from 712 individuals of the German KORA F4 cohort. Correlation-based analysis identified 1,109 significant associations between 522 transcripts and 114 metabolites summarized in an integrated network, the ‘human blood metabolome-transcriptome interface’ (BMTI). Bidirectional causality analysis using Mendelian randomization did not yield any statistically significant causal associations between transcripts and metabolites. A knowledge-based interpretation and integration with a genome-scale human metabolic reconstruction revealed systematic signatures of signaling, transport and metabolic processes, i.e. metabolic reactions mainly belonging to lipid, energy and amino acid metabolism. Moreover, the construction of a network based on functional categories illustrated the cross-talk between the biological layers at a pathway level. Using a transcription factor binding site enrichment analysis, this pathway cross-talk was further confirmed at a regulatory level. Finally, we demonstrated how the constructed networks can be used to gain novel insights into molecular mechanisms associated to intermediate clinical traits. Overall, our results demonstrate the utility of a multi-omics integrative approach to understand the molecular mechanisms underlying both normal physiology and disease. PMID:26086077

Integrated Systems Biology Analysis of Transcriptomes Reveals Candidate Genes for Acidity Control in Developing Fruits of Sweet Orange (Citrus sinensis L. Osbeck).

PubMed

Huang, Dingquan; Zhao, Yihong; Cao, Minghao; Qiao, Liang; Zheng, Zhi-Liang

2016-01-01

Organic acids, such as citrate and malate, are important contributors for the sensory traits of fleshy fruits. Although their biosynthesis has been illustrated, regulatory mechanisms of acid accumulation remain to be dissected. To provide transcriptional architecture and identify candidate genes for citrate accumulation in fruits, we have selected for transcriptome analysis four varieties of sweet orange (Citrus sinensis L. Osbeck) with varying fruit acidity, Succari (acidless), Bingtang (low acid), and Newhall and Xinhui (normal acid). Fruits of these varieties at 45 days post anthesis (DPA), which corresponds to Stage I (cell division), had similar acidity, but they displayed differential acid accumulation at 142 DPA (Stage II, cell expansion). Transcriptomes of fruits at 45 and 142 DPA were profiled using RNA sequencing and analyzed with three different algorithms (Pearson correlation, gene coexpression network and surrogate variable analysis). Our network analysis shows that the acid-correlated genes belong to three distinct network modules. Several of these candidate fruit acidity genes encode regulatory proteins involved in transport (such as AHA10), degradation (such as APD2) and transcription (such as AIL6) and act as hubs in the citrate accumulation gene networks. Taken together, our integrated systems biology analysis has provided new insights into the fruit citrate accumulation gene network and led to the identification of candidate genes likely associated with the fruit acidity control.

Integrated Systems Biology Analysis of Transcriptomes Reveals Candidate Genes for Acidity Control in Developing Fruits of Sweet Orange (Citrus sinensis L. Osbeck)

PubMed Central

Huang, Dingquan; Zhao, Yihong; Cao, Minghao; Qiao, Liang; Zheng, Zhi-Liang

2016-01-01

Organic acids, such as citrate and malate, are important contributors for the sensory traits of fleshy fruits. Although their biosynthesis has been illustrated, regulatory mechanisms of acid accumulation remain to be dissected. To provide transcriptional architecture and identify candidate genes for citrate accumulation in fruits, we have selected for transcriptome analysis four varieties of sweet orange (Citrus sinensis L. Osbeck) with varying fruit acidity, Succari (acidless), Bingtang (low acid), and Newhall and Xinhui (normal acid). Fruits of these varieties at 45 days post anthesis (DPA), which corresponds to Stage I (cell division), had similar acidity, but they displayed differential acid accumulation at 142 DPA (Stage II, cell expansion). Transcriptomes of fruits at 45 and 142 DPA were profiled using RNA sequencing and analyzed with three different algorithms (Pearson correlation, gene coexpression network and surrogate variable analysis). Our network analysis shows that the acid-correlated genes belong to three distinct network modules. Several of these candidate fruit acidity genes encode regulatory proteins involved in transport (such as AHA10), degradation (such as APD2) and transcription (such as AIL6) and act as hubs in the citrate accumulation gene networks. Taken together, our integrated systems biology analysis has provided new insights into the fruit citrate accumulation gene network and led to the identification of candidate genes likely associated with the fruit acidity control. PMID:27092171

Tentacle Transcriptome and Venom Proteome of the Pacific Sea Nettle, Chrysaora fuscescens (Cnidaria: Scyphozoa).

PubMed

Ponce, Dalia; Brinkman, Diane L; Potriquet, Jeremy; Mulvenna, Jason

2016-04-05

Jellyfish venoms are rich sources of toxins designed to capture prey or deter predators, but they can also elicit harmful effects in humans. In this study, an integrated transcriptomic and proteomic approach was used to identify putative toxins and their potential role in the venom of the scyphozoan jellyfish Chrysaora fuscescens. A de novo tentacle transcriptome, containing more than 23,000 contigs, was constructed and used in proteomic analysis of C. fuscescens venom to identify potential toxins. From a total of 163 proteins identified in the venom proteome, 27 were classified as putative toxins and grouped into six protein families: proteinases, venom allergens, C-type lectins, pore-forming toxins, glycoside hydrolases and enzyme inhibitors. Other putative toxins identified in the transcriptome, but not the proteome, included additional proteinases as well as lipases and deoxyribonucleases. Sequence analysis also revealed the presence of ShKT domains in two putative venom proteins from the proteome and an additional 15 from the transcriptome, suggesting potential ion channel blockade or modulatory activities. Comparison of these potential toxins to those from other cnidarians provided insight into their possible roles in C. fuscescens venom and an overview of the diversity of potential toxin families in cnidarian venoms.

GeNNet: an integrated platform for unifying scientific workflows and graph databases for transcriptome data analysis

PubMed Central

Gadelha, Luiz; Ribeiro-Alves, Marcelo; Porto, Fábio

2017-01-01

There are many steps in analyzing transcriptome data, from the acquisition of raw data to the selection of a subset of representative genes that explain a scientific hypothesis. The data produced can be represented as networks of interactions among genes and these may additionally be integrated with other biological databases, such as Protein-Protein Interactions, transcription factors and gene annotation. However, the results of these analyses remain fragmented, imposing difficulties, either for posterior inspection of results, or for meta-analysis by the incorporation of new related data. Integrating databases and tools into scientific workflows, orchestrating their execution, and managing the resulting data and its respective metadata are challenging tasks. Additionally, a great amount of effort is equally required to run in-silico experiments to structure and compose the information as needed for analysis. Different programs may need to be applied and different files are produced during the experiment cycle. In this context, the availability of a platform supporting experiment execution is paramount. We present GeNNet, an integrated transcriptome analysis platform that unifies scientific workflows with graph databases for selecting relevant genes according to the evaluated biological systems. It includes GeNNet-Wf, a scientific workflow that pre-loads biological data, pre-processes raw microarray data and conducts a series of analyses including normalization, differential expression inference, clusterization and gene set enrichment analysis. A user-friendly web interface, GeNNet-Web, allows for setting parameters, executing, and visualizing the results of GeNNet-Wf executions. To demonstrate the features of GeNNet, we performed case studies with data retrieved from GEO, particularly using a single-factor experiment in different analysis scenarios. As a result, we obtained differentially expressed genes for which biological functions were analyzed. The results are integrated into GeNNet-DB, a database about genes, clusters, experiments and their properties and relationships. The resulting graph database is explored with queries that demonstrate the expressiveness of this data model for reasoning about gene interaction networks. GeNNet is the first platform to integrate the analytical process of transcriptome data with graph databases. It provides a comprehensive set of tools that would otherwise be challenging for non-expert users to install and use. Developers can add new functionality to components of GeNNet. The derived data allows for testing previous hypotheses about an experiment and exploring new ones through the interactive graph database environment. It enables the analysis of different data on humans, rhesus, mice and rat coming from Affymetrix platforms. GeNNet is available as an open source platform at https://github.com/raquele/GeNNet and can be retrieved as a software container with the command docker pull quelopes/gennet. PMID:28695067

GeNNet: an integrated platform for unifying scientific workflows and graph databases for transcriptome data analysis.

PubMed

Costa, Raquel L; Gadelha, Luiz; Ribeiro-Alves, Marcelo; Porto, Fábio

2017-01-01

There are many steps in analyzing transcriptome data, from the acquisition of raw data to the selection of a subset of representative genes that explain a scientific hypothesis. The data produced can be represented as networks of interactions among genes and these may additionally be integrated with other biological databases, such as Protein-Protein Interactions, transcription factors and gene annotation. However, the results of these analyses remain fragmented, imposing difficulties, either for posterior inspection of results, or for meta-analysis by the incorporation of new related data. Integrating databases and tools into scientific workflows, orchestrating their execution, and managing the resulting data and its respective metadata are challenging tasks. Additionally, a great amount of effort is equally required to run in-silico experiments to structure and compose the information as needed for analysis. Different programs may need to be applied and different files are produced during the experiment cycle. In this context, the availability of a platform supporting experiment execution is paramount. We present GeNNet, an integrated transcriptome analysis platform that unifies scientific workflows with graph databases for selecting relevant genes according to the evaluated biological systems. It includes GeNNet-Wf, a scientific workflow that pre-loads biological data, pre-processes raw microarray data and conducts a series of analyses including normalization, differential expression inference, clusterization and gene set enrichment analysis. A user-friendly web interface, GeNNet-Web, allows for setting parameters, executing, and visualizing the results of GeNNet-Wf executions. To demonstrate the features of GeNNet, we performed case studies with data retrieved from GEO, particularly using a single-factor experiment in different analysis scenarios. As a result, we obtained differentially expressed genes for which biological functions were analyzed. The results are integrated into GeNNet-DB, a database about genes, clusters, experiments and their properties and relationships. The resulting graph database is explored with queries that demonstrate the expressiveness of this data model for reasoning about gene interaction networks. GeNNet is the first platform to integrate the analytical process of transcriptome data with graph databases. It provides a comprehensive set of tools that would otherwise be challenging for non-expert users to install and use. Developers can add new functionality to components of GeNNet. The derived data allows for testing previous hypotheses about an experiment and exploring new ones through the interactive graph database environment. It enables the analysis of different data on humans, rhesus, mice and rat coming from Affymetrix platforms. GeNNet is available as an open source platform at https://github.com/raquele/GeNNet and can be retrieved as a software container with the command docker pull quelopes/gennet.

Integrative structural annotation of de novo RNA-Seq provides an accurate reference gene set of the enormous genome of the onion (Allium cepa L.).

PubMed

Kim, Seungill; Kim, Myung-Shin; Kim, Yong-Min; Yeom, Seon-In; Cheong, Kyeongchae; Kim, Ki-Tae; Jeon, Jongbum; Kim, Sunggil; Kim, Do-Sun; Sohn, Seong-Han; Lee, Yong-Hwan; Choi, Doil

2015-02-01

The onion (Allium cepa L.) is one of the most widely cultivated and consumed vegetable crops in the world. Although a considerable amount of onion transcriptome data has been deposited into public databases, the sequences of the protein-coding genes are not accurate enough to be used, owing to non-coding sequences intermixed with the coding sequences. We generated a high-quality, annotated onion transcriptome from de novo sequence assembly and intensive structural annotation using the integrated structural gene annotation pipeline (ISGAP), which identified 54,165 protein-coding genes among 165,179 assembled transcripts totalling 203.0 Mb by eliminating the intron sequences. ISGAP performed reliable annotation, recognizing accurate gene structures based on reference proteins, and ab initio gene models of the assembled transcripts. Integrative functional annotation and gene-based SNP analysis revealed a whole biological repertoire of genes and transcriptomic variation in the onion. The method developed in this study provides a powerful tool for the construction of reference gene sets for organisms based solely on de novo transcriptome data. Furthermore, the reference genes and their variation described here for the onion represent essential tools for molecular breeding and gene cloning in Allium spp. © The Author 2014. Published by Oxford University Press on behalf of Kazusa DNA Research Institute.

Integrated whole-genome and transcriptome sequence analysis reveals the genetic characteristics of a riboflavin-overproducing Bacillus subtilis.

PubMed

Wang, Guanglu; Shi, Ting; Chen, Tao; Wang, Xiaoyue; Wang, Yongcheng; Liu, Dingyu; Guo, Jiaxin; Fu, Jing; Feng, Lili; Wang, Zhiwen; Zhao, Xueming

2018-06-02

Commercial riboflavin production with Bacillus subtilis has been developed by combining rational and classical strain development for almost two decades, but how an improved riboflavin producer can be created rationally is still not completely understood. In this study, we demonstrate the combined use of integrated genomic and transcriptomic analysis of the genetic basis for riboflavin over-production in B. subtilis. This methodology succeeded in discerning the positive mutations in the mutagenesis derived riboflavin producer B. subtilis 24/pMX45 through whole-genome sequencing and transcriptome sequencing. These included RibC (G199D), ribD + (G+39A), PurA (P242L), CcpN(A44S), YvrH (R222Q) and two nonsense mutations YhcF (R90*) and YwaA (Q68*). Reintroducing these specific mutations into the wild-type strain recovered the riboflavin overproduction phenotype and subsequent metabolic engineering greatly improved riboflavin production, achieving an up to 3.4-fold increase of the riboflavin titer over the sequenced producer. A novel mutation, YvrH (R222Q), involved in a typical two-component regulatory system deregulated the purine de novo synthesis pathway and increased the pool of intracellular purine metabolites, which in turn increased riboflavin production. Taken together, we present a case study of combining genome and transcriptome analysis to elucidate the genetic underpinnings of a complex cellular property, which enabled the transfer of beneficial mutations to engineer a reference strain into an overproducer. Copyright © 2018 International Metabolic Engineering Society. Published by Elsevier Inc. All rights reserved.

Integrated analysis of transcriptomic and metabolomic data reveals critical metabolic pathways involved in rotenoid biosynthesis in the medicinal plant Mirabilis himalaica.

PubMed

Gu, Li; Zhang, Zhong-Yi; Quan, Hong; Li, Ming-Jie; Zhao, Fang-Yu; Xu, Yuan-Jiang; Liu, Jiang; Sai, Man; Zheng, Wei-Lie; Lan, Xiao-Zhong

2018-06-01

Mirabilis himalaica (Edgew.) Heimerl is among the most important genuine medicinal plants in Tibet. However, the biosynthesis mechanisms of the active compounds in this species are unclear, severely limiting its application. To clarify the molecular biosynthesis mechanism of the key representative active compounds, specifically rotenoid, which is of special medicinal value for M. himalaica, RNA sequencing and TOF-MS technologies were used to construct transcriptomic and metabolomic libraries from the roots, stems, and leaves of M. himalaica plants collected from their natural habitat. As a result, each of the transcriptomic libraries from the different tissues was sequenced, generating more than 10 Gb of clean data ultimately assembled into 147,142 unigenes. In the three tissues, metabolomic analysis identified 522 candidate compounds, of which 170 metabolites involved in 114 metabolic pathways were mapped to the KEGG. Of these genes, 61 encoding enzymes were identified to function at key steps of the pathways related to rotenoid biosynthesis, where 14 intermediate metabolites were also located. An integrated analysis of metabolic and transcriptomic data revealed that most of the intermediate metabolites and enzymes related to rotenoid biosynthesis were synthesized in the roots, stems and leaves of M. himalaica, which suggested that the use of non-medicinal tissues to extract compounds was feasible. In addition, the CHS and CHI genes were found to play important roles in rotenoid biosynthesis, especially, since CHS might be an important rate-limiting enzyme. This study provides a hypothetical basis for the screening of new active metabolites and the metabolic engineering of rotenoid in M. himalaica.

Integrated analysis of transcriptome and lipid profiling reveals the co-influences of inositol-choline and Snf1 in controlling lipid biosynthesis in yeast.

PubMed

Chumnanpuen, Pramote; Zhang, Jie; Nookaew, Intawat; Nielsen, Jens

2012-07-01

In the yeast Saccharomyces cerevisiae many genes involved in lipid biosynthesis are transcriptionally controlled by inositol-choline and the protein kinase Snf1. Here we undertook a global study on how inositol-choline and Snf1 interact in controlling lipid metabolism in yeast. Using both a reference strain (CEN.PK113-7D) and a snf1Δ strain cultured at different nutrient limitations (carbon and nitrogen), at a fixed specific growth rate of 0.1 h(-1), and at different inositol choline concentrations, we quantified the expression of genes involved in lipid biosynthesis and the fluxes towards the different lipid components. Through integrated analysis of the transcriptome, the lipid profiling and the fluxome, it was possible to obtain a high quality, large-scale dataset that could be used to identify correlations and associations between the different components. At the transcription level, Snf1 and inositol-choline interact either directly through the main phospholipid-involving transcription factors (i.e. Ino2, Ino4, and Opi1) or through other transcription factors e.g. Gis1, Mga2, and Hac1. However, there seems to be flux regulation at the enzyme levels of several lipid involving enzymes. The analysis showed the strength of using both transcriptome and lipid profiling analysis for mapping the co-influence of inositol-choline and Snf1 on phospholipid metabolism.

Translational genomics for analysis of complex traits in peanut and sorghum

USDA-ARS?s Scientific Manuscript database

The integration of sequencing and genotype data from natural variation studies (by whole genome resequencing [wgs] or genotype by sequencing [gbs]), transcriptome (RNA-seq) and mutant analysis (also by wgs) facilitated the development of DNA markers in the form of single nucleotide polymorphic (SNP)...

EUCANEXT: an integrated database for the exploration of genomic and transcriptomic data from Eucalyptus species

PubMed Central

Nascimento, Leandro Costa; Salazar, Marcela Mendes; Lepikson-Neto, Jorge; Camargo, Eduardo Leal Oliveira; Parreiras, Lucas Salera; Carazzolle, Marcelo Falsarella

2017-01-01

Abstract Tree species of the genus Eucalyptus are the most valuable and widely planted hardwoods in the world. Given the economic importance of Eucalyptus trees, much effort has been made towards the generation of specimens with superior forestry properties that can deliver high-quality feedstocks, customized to the industrýs needs for both cellulosic (paper) and lignocellulosic biomass production. In line with these efforts, large sets of molecular data have been generated by several scientific groups, providing invaluable information that can be applied in the development of improved specimens. In order to fully explore the potential of available datasets, the development of a public database that provides integrated access to genomic and transcriptomic data from Eucalyptus is needed. EUCANEXT is a database that analyses and integrates publicly available Eucalyptus molecular data, such as the E. grandis genome assembly and predicted genes, ESTs from several species and digital gene expression from 26 RNA-Seq libraries. The database has been implemented in a Fedora Linux machine running MySQL and Apache, while Perl CGI was used for the web interfaces. EUCANEXT provides a user-friendly web interface for easy access and analysis of publicly available molecular data from Eucalyptus species. This integrated database allows for complex searches by gene name, keyword or sequence similarity and is publicly accessible at http://www.lge.ibi.unicamp.br/eucalyptusdb. Through EUCANEXT, users can perform complex analysis to identify genes related traits of interest using RNA-Seq libraries and tools for differential expression analysis. Moreover, all the bioinformatics pipeline here described, including the database schema and PERL scripts, are readily available and can be applied to any genomic and transcriptomic project, regardless of the organism. Database URL: http://www.lge.ibi.unicamp.br/eucalyptusdb PMID:29220468

CBrowse: a SAM/BAM-based contig browser for transcriptome assembly visualization and analysis.

PubMed

Li, Pei; Ji, Guoli; Dong, Min; Schmidt, Emily; Lenox, Douglas; Chen, Liangliang; Liu, Qi; Liu, Lin; Zhang, Jie; Liang, Chun

2012-09-15

To address the impending need for exploring rapidly increased transcriptomics data generated for non-model organisms, we developed CBrowse, an AJAX-based web browser for visualizing and analyzing transcriptome assemblies and contigs. Designed in a standard three-tier architecture with a data pre-processing pipeline, CBrowse is essentially a Rich Internet Application that offers many seamlessly integrated web interfaces and allows users to navigate, sort, filter, search and visualize data smoothly. The pre-processing pipeline takes the contig sequence file in FASTA format and its relevant SAM/BAM file as the input; detects putative polymorphisms, simple sequence repeats and sequencing errors in contigs and generates image, JSON and database-compatible CSV text files that are directly utilized by different web interfaces. CBowse is a generic visualization and analysis tool that facilitates close examination of assembly quality, genetic polymorphisms, sequence repeats and/or sequencing errors in transcriptome sequencing projects. CBrowse is distributed under the GNU General Public License, available at http://bioinfolab.muohio.edu/CBrowse/ liangc@muohio.edu or liangc.mu@gmail.com; glji@xmu.edu.cn Supplementary data are available at Bioinformatics online.

Transcriptome analysis and related databases of Lactococcus lactis.

PubMed

Kuipers, Oscar P; de Jong, Anne; Baerends, Richard J S; van Hijum, Sacha A F T; Zomer, Aldert L; Karsens, Harma A; den Hengst, Chris D; Kramer, Naomi E; Buist, Girbe; Kok, Jan

2002-08-01

Several complete genome sequences of Lactococcus lactis and their annotations will become available in the near future, next to the already published genome sequence of L. lactis ssp. lactis IL 1403. This will allow intraspecies comparative genomics studies as well as functional genomics studies aimed at a better understanding of physiological processes and regulatory networks operating in lactococci. This paper describes the initial set-up of a DNA-microarray facility in our group, to enable transcriptome analysis of various Gram-positive bacteria, including a ssp. lactis and a ssp. cremoris strain of Lactococcus lactis. Moreover a global description will be given of the hardware and software requirements for such a set-up, highlighting the crucial integration of relevant bioinformatics tools and methods. This includes the development of MolGenIS, an information system for transcriptome data storage and retrieval, and LactococCye, a metabolic pathway/genome database of Lactococcus lactis.

Blood transcriptomics and metabolomics for personalized medicine.

PubMed

Li, Shuzhao; Todor, Andrei; Luo, Ruiyan

2016-01-01

Molecular analysis of blood samples is pivotal to clinical diagnosis and has been intensively investigated since the rise of systems biology. Recent developments have opened new opportunities to utilize transcriptomics and metabolomics for personalized and precision medicine. Efforts from human immunology have infused into this area exquisite characterizations of subpopulations of blood cells. It is now possible to infer from blood transcriptomics, with fine accuracy, the contribution of immune activation and of cell subpopulations. In parallel, high-resolution mass spectrometry has brought revolutionary analytical capability, detecting > 10,000 metabolites, together with environmental exposure, dietary intake, microbial activity, and pharmaceutical drugs. Thus, the re-examination of blood chemicals by metabolomics is in order. Transcriptomics and metabolomics can be integrated to provide a more comprehensive understanding of the human biological states. We will review these new data and methods and discuss how they can contribute to personalized medicine.

Transcriptome Meta-Analysis of Lung Cancer Reveals Recurrent Aberrations in NRG1 and Hippo Pathway Genes

PubMed Central

Dhanasekaran, Saravana M.; Balbin, O. Alejandro; Chen, Guoan; Nadal, Ernest; Kalyana-Sundaram, Shanker; Pan, Jincheng; Veeneman, Brendan; Cao, Xuhong; Malik, Rohit; Vats, Pankaj; Wang, Rui; Huang, Stephanie; Zhong, Jinjie; Jing, Xiaojun; Iyer, Matthew; Wu, Yi-Mi; Harms, Paul W.; Lin, Jules; Reddy, Rishindra; Brennan, Christine; Palanisamy, Nallasivam; Chang, Andrew C.; Truini, Anna; Truini, Mauro; Robinson, Dan R.; Beer, David G.; Chinnaiyan, Arul M.

2014-01-01

Lung cancer is emerging as a paradigm for disease molecular subtyping, facilitating targeted therapy based on driving somatic alterations. Here, we perform transcriptome analysis of 153 samples representing lung adenocarcinomas, squamous cell carcinomas, large cell lung cancer, adenoid cystic carcinomas and cell lines. By integrating our data with The Cancer Genome Atlas and published sources, we analyze 753 lung cancer samples for gene fusions and other transcriptomic alterations. We show that higher numbers of gene fusions is an independent prognostic factor for poor survival in lung cancer. Our analysis confirms the recently reported CD74-NRG1 fusion and suggests that NRG1, NF1 and Hippo pathway fusions may play important roles in tumors without known driver mutations. In addition, we observe exon skipping events in c-MET, which are attributable to splice site mutations. These classes of genetic aberrations may play a significant role in the genesis of lung cancers lacking known driver mutations. PMID:25531467

Transcriptomics-based strain optimization tool for designing secondary metabolite overproducing strains of Streptomyces coelicolor.

PubMed

Kim, Minsuk; Yi, Jeong Sang; Lakshmanan, Meiyappan; Lee, Dong-Yup; Kim, Byung-Gee

2016-03-01

In silico model-driven analysis using genome-scale model of metabolism (GEM) has been recognized as a promising method for microbial strain improvement. However, most of the current GEM-based strain design algorithms based on flux balance analysis (FBA) heavily rely on the steady-state and optimality assumptions without considering any regulatory information. Thus, their practical usage is quite limited, especially in its application to secondary metabolites overproduction. In this study, we developed a transcriptomics-based strain optimization tool (tSOT) in order to overcome such limitations by integrating transcriptomic data into GEM. Initially, we evaluated existing algorithms for integrating transcriptomic data into GEM using Streptomyces coelicolor dataset, and identified iMAT algorithm as the only and the best algorithm for characterizing the secondary metabolism of S. coelicolor. Subsequently, we developed tSOT platform where iMAT is adopted to predict the reaction states, and successfully demonstrated its applicability to secondary metabolites overproduction by designing actinorhodin (ACT), a polyketide antibiotic, overproducing strain of S. coelicolor. Mutants overexpressing tSOT targets such as ribulose 5-phosphate 3-epimerase and NADP-dependent malic enzyme showed 2 and 1.8-fold increase in ACT production, thereby validating the tSOT prediction. It is expected that tSOT can be used for solving other metabolic engineering problems which could not be addressed by current strain design algorithms, especially for the secondary metabolite overproductions. © 2015 Wiley Periodicals, Inc.

Integrated analysis of 454 and Illumina transcriptomic sequencing characterizes carbon flux and energy source for fatty acid synthesis in developing Lindera glauca fruits for woody biodiesel.

PubMed

Lin, Zixin; An, Jiyong; Wang, Jia; Niu, Jun; Ma, Chao; Wang, Libing; Yuan, Guanshen; Shi, Lingling; Liu, Lili; Zhang, Jinsong; Zhang, Zhixiang; Qi, Ji; Lin, Shanzhi

2017-01-01

Lindera glauca fruit with high quality and quantity of oil has emerged as a novel potential source of biodiesel in China, but the molecular regulatory mechanism of carbon flux and energy source for oil biosynthesis in developing fruits is still unknown. To better develop fruit oils of L. glauca as woody biodiesel, a combination of two different sequencing platforms (454 and Illumina) and qRT-PCR analysis was used to define a minimal reference transcriptome of developing L. glauca fruits, and to construct carbon and energy metabolic model for regulation of carbon partitioning and energy supply for FA biosynthesis and oil accumulation. We first analyzed the dynamic patterns of growth tendency, oil content, FA compositions, biodiesel properties, and the contents of ATP and pyridine nucleotide of L. glauca fruits from seven different developing stages. Comprehensive characterization of transcriptome of the developing L. glauca fruit was performed using a combination of two different next-generation sequencing platforms, of which three representative fruit samples (50, 125, and 150 DAF) and one mixed sample from seven developing stages were selected for Illumina and 454 sequencing, respectively. The unigenes separately obtained from long and short reads (201, and 259, respectively, in total) were reconciled using TGICL software, resulting in a total of 60,031 unigenes (mean length = 1061.95 bp) to describe a transcriptome for developing L. glauca fruits. Notably, 198 genes were annotated for photosynthesis, sucrose cleavage, carbon allocation, metabolite transport, acetyl-CoA formation, oil synthesis, and energy metabolism, among which some specific transporters, transcription factors, and enzymes were identified to be implicated in carbon partitioning and energy source for oil synthesis by an integrated analysis of transcriptomic sequencing and qRT-PCR. Importantly, the carbon and energy metabolic model was well established for oil biosynthesis of developing L. glauca fruits, which could help to reveal the molecular regulatory mechanism of the increased oil production in developing fruits. This study presents for the first time the application of an integrated two different sequencing analyses (Illumina and 454) and qRT-PCR detection to define a minimal reference transcriptome for developing L. glauca fruits, and to elucidate the molecular regulatory mechanism of carbon flux control and energy provision for oil synthesis. Our results will provide a valuable resource for future fundamental and applied research on the woody biodiesel plants.

Tentacle Transcriptome and Venom Proteome of the Pacific Sea Nettle, Chrysaora fuscescens (Cnidaria: Scyphozoa)

PubMed Central

Ponce, Dalia; Brinkman, Diane L.; Potriquet, Jeremy; Mulvenna, Jason

2016-01-01

Jellyfish venoms are rich sources of toxins designed to capture prey or deter predators, but they can also elicit harmful effects in humans. In this study, an integrated transcriptomic and proteomic approach was used to identify putative toxins and their potential role in the venom of the scyphozoan jellyfish Chrysaora fuscescens. A de novo tentacle transcriptome, containing more than 23,000 contigs, was constructed and used in proteomic analysis of C. fuscescens venom to identify potential toxins. From a total of 163 proteins identified in the venom proteome, 27 were classified as putative toxins and grouped into six protein families: proteinases, venom allergens, C-type lectins, pore-forming toxins, glycoside hydrolases and enzyme inhibitors. Other putative toxins identified in the transcriptome, but not the proteome, included additional proteinases as well as lipases and deoxyribonucleases. Sequence analysis also revealed the presence of ShKT domains in two putative venom proteins from the proteome and an additional 15 from the transcriptome, suggesting potential ion channel blockade or modulatory activities. Comparison of these potential toxins to those from other cnidarians provided insight into their possible roles in C. fuscescens venom and an overview of the diversity of potential toxin families in cnidarian venoms. PMID:27058558

Large-scale atlas of microarray data reveals the distinct expression landscape of different tissues in Arabidopsis

DOE Office of Scientific and Technical Information (OSTI.GOV)

He, Fei; Maslov, Sergei; Yoo, Shinjae

Here, transcriptome datasets from thousands of samples of the model plant Arabidopsis thaliana have been collectively generated by multiple individual labs. Although integration and meta-analysis of these samples has become routine in the plant research community, it is often hampered by the lack of metadata or differences in annotation styles by different labs. In this study, we carefully selected and integrated 6,057 Arabidopsis microarray expression samples from 304 experiments deposited to NCBI GEO. Metadata such as tissue type, growth condition, and developmental stage were manually curated for each sample. We then studied global expression landscape of the integrated dataset andmore » found that samples of the same tissue tend to be more similar to each other than to samples of other tissues, even in different growth conditions or developmental stages. Root has the most distinct transcriptome compared to aerial tissues, but the transcriptome of cultured root is more similar to those of aerial tissues as the former samples lost their cellular identity. Using a simple computational classification method, we showed that the tissue type of a sample can be successfully predicted based on its expression profile, opening the door for automatic metadata extraction and facilitating re-use of plant transcriptome data. As a proof of principle we applied our automated annotation pipeline to 708 RNA-seq samples from public repositories and verified accuracy of our predictions with samples’ metadata provided by authors.« less

Large-scale atlas of microarray data reveals the distinct expression landscape of different tissues in Arabidopsis

DOE PAGES

He, Fei; Maslov, Sergei; Yoo, Shinjae; ...

2016-05-25

Here, transcriptome datasets from thousands of samples of the model plant Arabidopsis thaliana have been collectively generated by multiple individual labs. Although integration and meta-analysis of these samples has become routine in the plant research community, it is often hampered by the lack of metadata or differences in annotation styles by different labs. In this study, we carefully selected and integrated 6,057 Arabidopsis microarray expression samples from 304 experiments deposited to NCBI GEO. Metadata such as tissue type, growth condition, and developmental stage were manually curated for each sample. We then studied global expression landscape of the integrated dataset andmore » found that samples of the same tissue tend to be more similar to each other than to samples of other tissues, even in different growth conditions or developmental stages. Root has the most distinct transcriptome compared to aerial tissues, but the transcriptome of cultured root is more similar to those of aerial tissues as the former samples lost their cellular identity. Using a simple computational classification method, we showed that the tissue type of a sample can be successfully predicted based on its expression profile, opening the door for automatic metadata extraction and facilitating re-use of plant transcriptome data. As a proof of principle we applied our automated annotation pipeline to 708 RNA-seq samples from public repositories and verified accuracy of our predictions with samples’ metadata provided by authors.« less

Role of TGF Beta and PPAR Alpha Signaling Pathways in Radiation Response of Locally Exposed Heart: Integrated Global Transcriptomics and Proteomics Analysis.

PubMed

Subramanian, Vikram; Seemann, Ingar; Merl-Pham, Juliane; Hauck, Stefanie M; Stewart, Fiona A; Atkinson, Michael J; Tapio, Soile; Azimzadeh, Omid

2017-01-06

Epidemiological data from patients undergoing radiotherapy for thoracic tumors clearly show the damaging effect of ionizing radiation on cardiovascular system. The long-term impairment of heart function and structure after local high-dose irradiation is associated with systemic inflammatory response, contraction impairment, microvascular damage, and cardiac fibrosis. The goal of the present study was to investigate molecular mechanisms involved in this process. C57BL/6J mice received a single X-ray dose of 16 Gy given locally to the heart at the age of 8 weeks. Radiation-induced changes in the heart transcriptome and proteome were investigated 40 weeks after the exposure. The omics data were analyzed by bioinformatics tools and validated by immunoblotting. Integrated network analysis of transcriptomics and proteomics data elucidated the signaling pathways that were similarly affected at gene and protein level. Analysis showed induction of transforming growth factor (TGF) beta signaling but inactivation of peroxisome proliferator-activated receptor (PPAR) alpha signaling in irradiated heart. The putative mediator role of mitogen-activated protein kinase cascade linking PPAR alpha and TGF beta signaling was supported by data from immunoblotting and ELISA. This study indicates that both signaling pathways are involved in radiation-induced heart fibrosis, metabolic disordering, and impaired contractility, a pathophysiological condition that is often observed in patients that received high radiation doses in thorax.

Integrity of Induced Pluripotent Stem Cell (iPSC) Derived Megakaryocytes as Assessed by Genetic and Transcriptomic Analysis

PubMed Central

Kammers, Kai; Taub, Margaret A.; Ruczinski, Ingo; Martin, Joshua; Yanek, Lisa R.; Frazee, Alyssa; Gao, Yongxing; Hoyle, Dixie; Faraday, Nauder; Becker, Diane M.; Cheng, Linzhao; Wang, Zack Z.; Leek, Jeff T.; Becker, Lewis C.; Mathias, Rasika A.

2017-01-01

Previously, we have described our feeder-free, xeno-free approach to generate megakaryocytes (MKs) in culture from human induced pluripotent stem cells (iPSCs). Here, we focus specifically on the integrity of these MKs using: (1) genotype discordance between parent cell DNA to iPSC cell DNA and onward to the differentiated MK DNA; (2) genomic structural integrity using copy number variation (CNV); and (3) transcriptomic signatures of the derived MK lines compared to the iPSC lines. We detected a very low rate of genotype discordance; estimates were 0.0001%-0.01%, well below the genotyping error rate for our assay (0.37%). No CNVs were generated in the iPSCs that were subsequently passed on to the MKs. Finally, we observed highly biologically relevant gene sets as being upregulated in MKs relative to the iPSCs: platelet activation, blood coagulation, megakaryocyte development, platelet formation, platelet degranulation, and platelet aggregation. These data strongly support the integrity of the derived MK lines. PMID:28107356

Integrated Quantitative Transcriptome Maps of Human Trisomy 21 Tissues and Cells

PubMed Central

Pelleri, Maria Chiara; Cattani, Chiara; Vitale, Lorenza; Antonaros, Francesca; Strippoli, Pierluigi; Locatelli, Chiara; Cocchi, Guido; Piovesan, Allison; Caracausi, Maria

2018-01-01

Down syndrome (DS) is due to the presence of an extra full or partial chromosome 21 (Hsa21). The identification of genes contributing to DS pathogenesis could be the key to any rational therapy of the associated intellectual disability. We aim at generating quantitative transcriptome maps in DS integrating all gene expression profile datasets available for any cell type or tissue, to obtain a complete model of the transcriptome in terms of both expression values for each gene and segmental trend of gene expression along each chromosome. We used the TRAM (Transcriptome Mapper) software for this meta-analysis, comparing transcript expression levels and profiles between DS and normal brain, lymphoblastoid cell lines, blood cells, fibroblasts, thymus and induced pluripotent stem cells, respectively. TRAM combined, normalized, and integrated datasets from different sources and across diverse experimental platforms. The main output was a linear expression value that may be used as a reference for each of up to 37,181 mapped transcripts analyzed, related to both known genes and expression sequence tag (EST) clusters. An independent example in vitro validation of fibroblast transcriptome map data was performed through “Real-Time” reverse transcription polymerase chain reaction showing an excellent correlation coefficient (r = 0.93, p < 0.0001) with data obtained in silico. The availability of linear expression values for each gene allowed the testing of the gene dosage hypothesis of the expected 3:2 DS/normal ratio for Hsa21 as well as other human genes in DS, in addition to listing genes differentially expressed with statistical significance. Although a fraction of Hsa21 genes escapes dosage effects, Hsa21 genes are selectively over-expressed in DS samples compared to genes from other chromosomes, reflecting a decisive role in the pathogenesis of the syndrome. Finally, the analysis of chromosomal segments reveals a high prevalence of Hsa21 over-expressed segments over the other genomic regions, suggesting, in particular, a specific region on Hsa21 that appears to be frequently over-expressed (21q22). Our complete datasets are released as a new framework to investigate transcription in DS for individual genes as well as chromosomal segments in different cell types and tissues. PMID:29740474

Integrated systems biology analysis of KSHV latent infection reveals viral induction and reliance on peroxisome mediated lipid metabolism

PubMed Central

Sychev, Zoi E.; Hu, Alex; Lagunoff, Michael

2017-01-01

Kaposi’s Sarcoma associated Herpesvirus (KSHV), an oncogenic, human gamma-herpesvirus, is the etiological agent of Kaposi’s Sarcoma the most common tumor of AIDS patients world-wide. KSHV is predominantly latent in the main KS tumor cell, the spindle cell, a cell of endothelial origin. KSHV modulates numerous host cell-signaling pathways to activate endothelial cells including major metabolic pathways involved in lipid metabolism. To identify the underlying cellular mechanisms of KSHV alteration of host signaling and endothelial cell activation, we identified changes in the host proteome, phosphoproteome and transcriptome landscape following KSHV infection of endothelial cells. A Steiner forest algorithm was used to integrate the global data sets and, together with transcriptome based predicted transcription factor activity, cellular networks altered by latent KSHV were predicted. Several interesting pathways were identified, including peroxisome biogenesis. To validate the predictions, we showed that KSHV latent infection increases the number of peroxisomes per cell. Additionally, proteins involved in peroxisomal lipid metabolism of very long chain fatty acids, including ABCD3 and ACOX1, are required for the survival of latently infected cells. In summary, novel cellular pathways altered during herpesvirus latency that could not be predicted by a single systems biology platform, were identified by integrated proteomics and transcriptomics data analysis and when correlated with our metabolomics data revealed that peroxisome lipid metabolism is essential for KSHV latent infection of endothelial cells. PMID:28257516

CAS-viewer: web-based tool for splicing-guided integrative analysis of multi-omics cancer data.

PubMed

Han, Seonggyun; Kim, Dongwook; Kim, Youngjun; Choi, Kanghoon; Miller, Jason E; Kim, Dokyoon; Lee, Younghee

2018-04-20

The Cancer Genome Atlas (TCGA) project is a public resource that provides transcriptomic, DNA sequence, methylation, and clinical data for 33 cancer types. Transforming the large size and high complexity of TCGA cancer genome data into integrated knowledge can be useful to promote cancer research. Alternative splicing (AS) is a key regulatory mechanism of genes in human cancer development and in the interaction with epigenetic factors. Therefore, AS-guided integration of existing TCGA data sets will make it easier to gain insight into the genetic architecture of cancer risk and related outcomes. There are already existing tools analyzing and visualizing alternative mRNA splicing patterns for large-scale RNA-seq experiments. However, these existing web-based tools are limited to the analysis of individual TCGA data sets at a time, such as only transcriptomic information. We implemented CAS-viewer (integrative analysis of Cancer genome data based on Alternative Splicing), a web-based tool leveraging multi-cancer omics data from TCGA. It illustrates alternative mRNA splicing patterns along with methylation, miRNAs, and SNPs, and then provides an analysis tool to link differential transcript expression ratio to methylation, miRNA, and splicing regulatory elements for 33 cancer types. Moreover, one can analyze AS patterns with clinical data to identify potential transcripts associated with different survival outcome for each cancer. CAS-viewer is a web-based application for transcript isoform-driven integration of multi-omics data in multiple cancer types and will aid in the visualization and possible discovery of biomarkers for cancer by integrating multi-omics data from TCGA.

The genomic and transcriptomic architecture of 2,000 breast tumours reveals novel subgroups.

PubMed

Curtis, Christina; Shah, Sohrab P; Chin, Suet-Feung; Turashvili, Gulisa; Rueda, Oscar M; Dunning, Mark J; Speed, Doug; Lynch, Andy G; Samarajiwa, Shamith; Yuan, Yinyin; Gräf, Stefan; Ha, Gavin; Haffari, Gholamreza; Bashashati, Ali; Russell, Roslin; McKinney, Steven; Langerød, Anita; Green, Andrew; Provenzano, Elena; Wishart, Gordon; Pinder, Sarah; Watson, Peter; Markowetz, Florian; Murphy, Leigh; Ellis, Ian; Purushotham, Arnie; Børresen-Dale, Anne-Lise; Brenton, James D; Tavaré, Simon; Caldas, Carlos; Aparicio, Samuel

2012-04-18

The elucidation of breast cancer subgroups and their molecular drivers requires integrated views of the genome and transcriptome from representative numbers of patients. We present an integrated analysis of copy number and gene expression in a discovery and validation set of 997 and 995 primary breast tumours, respectively, with long-term clinical follow-up. Inherited variants (copy number variants and single nucleotide polymorphisms) and acquired somatic copy number aberrations (CNAs) were associated with expression in ~40% of genes, with the landscape dominated by cis- and trans-acting CNAs. By delineating expression outlier genes driven in cis by CNAs, we identified putative cancer genes, including deletions in PPP2R2A, MTAP and MAP2K4. Unsupervised analysis of paired DNA–RNA profiles revealed novel subgroups with distinct clinical outcomes, which reproduced in the validation cohort. These include a high-risk, oestrogen-receptor-positive 11q13/14 cis-acting subgroup and a favourable prognosis subgroup devoid of CNAs. Trans-acting aberration hotspots were found to modulate subgroup-specific gene networks, including a TCR deletion-mediated adaptive immune response in the ‘CNA-devoid’ subgroup and a basal-specific chromosome 5 deletion-associated mitotic network. Our results provide a novel molecular stratification of the breast cancer population, derived from the impact of somatic CNAs on the transcriptome.

Combined analysis of DNA methylome and transcriptome reveal novel candidate genes with susceptibility to bovine Staphylococcus aureus subclinical mastitis.

PubMed

Song, Minyan; He, Yanghua; Zhou, Huangkai; Zhang, Yi; Li, Xizhi; Yu, Ying

2016-07-14

Subclinical mastitis is a widely spread disease of lactating cows. Its major pathogen is Staphylococcus aureus (S. aureus). In this study, we performed genome-wide integrative analysis of DNA methylation and transcriptional expression to identify candidate genes and pathways relevant to bovine S. aureus subclinical mastitis. The genome-scale DNA methylation profiles of peripheral blood lymphocytes in cows with S. aureus subclinical mastitis (SA group) and healthy controls (CK) were generated by methylated DNA immunoprecipitation combined with microarrays. We identified 1078 differentially methylated genes in SA cows compared with the controls. By integrating DNA methylation and transcriptome data, 58 differentially methylated genes were shared with differently expressed genes, in which 20.7% distinctly hypermethylated genes showed down-regulated expression in SA versus CK, whereas 14.3% dramatically hypomethylated genes showed up-regulated expression. Integrated pathway analysis suggested that these genes were related to inflammation, ErbB signalling pathway and mismatch repair. Further functional analysis revealed that three genes, NRG1, MST1 and NAT9, were strongly correlated with the progression of S. aureus subclinical mastitis and could be used as powerful biomarkers for the improvement of bovine mastitis resistance. Our studies lay the groundwork for epigenetic modification and mechanistic studies on susceptibility of bovine mastitis.

Combined analysis of DNA methylome and transcriptome reveal novel candidate genes with susceptibility to bovine Staphylococcus aureus subclinical mastitis

PubMed Central

Song, Minyan; He, Yanghua; Zhou, Huangkai; Zhang, Yi; Li, Xizhi; Yu, Ying

2016-01-01

Subclinical mastitis is a widely spread disease of lactating cows. Its major pathogen is Staphylococcus aureus (S. aureus). In this study, we performed genome-wide integrative analysis of DNA methylation and transcriptional expression to identify candidate genes and pathways relevant to bovine S. aureus subclinical mastitis. The genome-scale DNA methylation profiles of peripheral blood lymphocytes in cows with S. aureus subclinical mastitis (SA group) and healthy controls (CK) were generated by methylated DNA immunoprecipitation combined with microarrays. We identified 1078 differentially methylated genes in SA cows compared with the controls. By integrating DNA methylation and transcriptome data, 58 differentially methylated genes were shared with differently expressed genes, in which 20.7% distinctly hypermethylated genes showed down-regulated expression in SA versus CK, whereas 14.3% dramatically hypomethylated genes showed up-regulated expression. Integrated pathway analysis suggested that these genes were related to inflammation, ErbB signalling pathway and mismatch repair. Further functional analysis revealed that three genes, NRG1, MST1 and NAT9, were strongly correlated with the progression of S. aureus subclinical mastitis and could be used as powerful biomarkers for the improvement of bovine mastitis resistance. Our studies lay the groundwork for epigenetic modification and mechanistic studies on susceptibility of bovine mastitis. PMID:27411928

Veterinary Medicine and Multi-Omics Research for Future Nutrition Targets: Metabolomics and Transcriptomics of the Common Degenerative Mitral Valve Disease in Dogs.

PubMed

Li, Qinghong; Freeman, Lisa M; Rush, John E; Huggins, Gordon S; Kennedy, Adam D; Labuda, Jeffrey A; Laflamme, Dorothy P; Hannah, Steven S

2015-08-01

Canine degenerative mitral valve disease (DMVD) is the most common form of heart disease in dogs. The objective of this study was to identify cellular and metabolic pathways that play a role in DMVD by performing metabolomics and transcriptomics analyses on serum and tissue (mitral valve and left ventricle) samples previously collected from dogs with DMVD or healthy hearts. Gas or liquid chromatography followed by mass spectrophotometry were used to identify metabolites in serum. Transcriptomics analysis of tissue samples was completed using RNA-seq, and selected targets were confirmed by RT-qPCR. Random Forest analysis was used to classify the metabolites that best predicted the presence of DMVD. Results identified 41 known and 13 unknown serum metabolites that were significantly different between healthy and DMVD dogs, representing alterations in fat and glucose energy metabolism, oxidative stress, and other pathways. The three metabolites with the greatest single effect in the Random Forest analysis were γ-glutamylmethionine, oxidized glutathione, and asymmetric dimethylarginine. Transcriptomics analysis identified 812 differentially expressed transcripts in left ventricle samples and 263 in mitral valve samples, representing changes in energy metabolism, antioxidant function, nitric oxide signaling, and extracellular matrix homeostasis pathways. Many of the identified alterations may benefit from nutritional or medical management. Our study provides evidence of the growing importance of integrative approaches in multi-omics research in veterinary and nutritional sciences.

Selenium supplementation prevents metabolic and transcriptomic responses to cadmium in mouse lung.

PubMed

Hu, Xin; Chandler, Joshua D; Fernandes, Jolyn; Orr, Michael L; Hao, Li; Uppal, Karan; Neujahr, David C; Jones, Dean P; Go, Young-Mi

2018-04-12

The protective effect of selenium (Se) on cadmium (Cd) toxicity is well documented, but underlying mechanisms are unclear. Male mice fed standard diet were given Cd (CdCl 2 , 18 μmol/L) in drinking water with or without Se (Na 2 SeO 4, 20 μmol/L) for 16 weeks. Lungs were analyzed for Cd concentration, transcriptomics and metabolomics. Data were analyzed with biostatistics, bioinformatics, pathway enrichment analysis, and combined transcriptome-metabolome-wide association study. Mice treated with Cd had higher lung Cd content (1.7 ± 0.4 pmol/mg protein) than control mice (0.8 ± 0.3 pmol/mg protein) or mice treated with Cd and Se (0.4 ± 0.1 pmol/mg protein). Gene set enrichment analysis of transcriptomics data showed that Se prevented Cd effects on inflammatory and myogenesis genes and diminished Cd effects on several other pathways. Similarly, Se prevented Cd-disrupted metabolic pathways in amino acid metabolism and urea cycle. Integrated transcriptome and metabolome network analysis showed that Cd treatment had a network structure with fewer gene-metabolite clusters compared to control. Centrality measurements showed that Se counteracted changes in a group of Cd-responsive genes including Zdhhc11, (protein-cysteine S-palmitoyltransferase), Ighg1 (immunoglobulin heavy constant gamma-1) and associated changes in metabolite concentrations. Co-administration of Se with Cd prevented Cd increase in lung and prevented Cd-associated pathway and network responses of the transcriptome and metabolome. Se protection against Cd toxicity in lung involves complex systems responses. Environmental Cd stimulates proinflammatory and profibrotic signaling. The present results indicate that dietary or supplemental Se could be useful to mitigate Cd toxicity. Published by Elsevier B.V.

Multi-Omics Driven Assembly and Annotation of the Sandalwood (Santalum album) Genome.

PubMed

Mahesh, Hirehally Basavarajegowda; Subba, Pratigya; Advani, Jayshree; Shirke, Meghana Deepak; Loganathan, Ramya Malarini; Chandana, Shankara Lingu; Shilpa, Siddappa; Chatterjee, Oishi; Pinto, Sneha Maria; Prasad, Thottethodi Subrahmanya Keshava; Gowda, Malali

2018-04-01

Indian sandalwood ( Santalum album ) is an important tropical evergreen tree known for its fragrant heartwood-derived essential oil and its valuable carving wood. Here, we applied an integrated genomic, transcriptomic, and proteomic approach to assemble and annotate the Indian sandalwood genome. Our genome sequencing resulted in the establishment of a draft map of the smallest genome for any woody tree species to date (221 Mb). The genome annotation predicted 38,119 protein-coding genes and 27.42% repetitive DNA elements. In-depth proteome analysis revealed the identities of 72,325 unique peptides, which confirmed 10,076 of the predicted genes. The addition of transcriptomic and proteogenomic approaches resulted in the identification of 53 novel proteins and 34 gene-correction events that were missed by genomic approaches. Proteogenomic analysis also helped in reassigning 1,348 potential noncoding RNAs as bona fide protein-coding messenger RNAs. Gene expression patterns at the RNA and protein levels indicated that peptide sequencing was useful in capturing proteins encoded by nuclear and organellar genomes alike. Mass spectrometry-based proteomic evidence provided an unbiased approach toward the identification of proteins encoded by organellar genomes. Such proteins are often missed in transcriptome data sets due to the enrichment of only messenger RNAs that contain poly(A) tails. Overall, the use of integrated omic approaches enhanced the quality of the assembly and annotation of this nonmodel plant genome. The availability of genomic, transcriptomic, and proteomic data will enhance genomics-assisted breeding, germplasm characterization, and conservation of sandalwood trees. © 2018 American Society of Plant Biologists. All Rights Reserved.

Harnessing pain heterogeneity and RNA transcriptome to identify blood–based pain biomarkers: a novel correlational study design and bioinformatics approach in a graded chronic constriction injury model

PubMed Central

Grace, Peter M.; Hurley, Daniel; Barratt, Daniel T.; Tsykin, Anna; Watkins, Linda R.; Rolan, Paul E.; Hutchinson, Mark R.

2017-01-01

A quantitative, peripherally accessible biomarker for neuropathic pain has great potential to improve clinical outcomes. Based on the premise that peripheral and central immunity contribute to neuropathic pain mechanisms, we hypothesized that biomarkers could be identified from the whole blood of adult male rats, by integrating graded chronic constriction injury (CCI), ipsilateral lumbar dorsal quadrant (iLDQ) and whole blood transcriptomes, and pathway analysis with pain behavior. Correlational bioinformatics identified a range of putative biomarker genes for allodynia intensity, many encoding for proteins with a recognized role in immune/nociceptive mechanisms. A selection of these genes was validated in a separate replication study. Pathway analysis of the iLDQ transcriptome identified Fcγ and Fcε signaling pathways, among others. This study is the first to employ the whole blood transcriptome to identify pain biomarker panels. The novel correlational bioinformatics, developed here, selected such putative biomarkers based on a correlation with pain behavior and formation of signaling pathways with iLDQ genes. Future studies may demonstrate the predictive ability of these biomarker genes across other models and additional variables. PMID:22697386

Integrated network analysis and effective tools in plant systems biology

PubMed Central

Fukushima, Atsushi; Kanaya, Shigehiko; Nishida, Kozo

2014-01-01

One of the ultimate goals in plant systems biology is to elucidate the genotype-phenotype relationship in plant cellular systems. Integrated network analysis that combines omics data with mathematical models has received particular attention. Here we focus on the latest cutting-edge computational advances that facilitate their combination. We highlight (1) network visualization tools, (2) pathway analyses, (3) genome-scale metabolic reconstruction, and (4) the integration of high-throughput experimental data and mathematical models. Multi-omics data that contain the genome, transcriptome, proteome, and metabolome and mathematical models are expected to integrate and expand our knowledge of complex plant metabolisms. PMID:25408696

An integrated proteomic and transcriptomic analysis of perivitelline fluid proteins in a freshwater gastropod laying aerial eggs.

PubMed

Mu, Huawei; Sun, Jin; Heras, Horacio; Chu, Ka Hou; Qiu, Jian-Wen

2017-02-23

Proteins of the egg perivitelline fluid (PVF) that surrounds the embryo are critical for embryonic development in many animals, but little is known about their identities. Using an integrated proteomic and transcriptomic approach, we identified 64 proteins from the PVF of Pomacea maculata, a freshwater snail adopting aerial oviposition. Proteins were classified into eight functional groups: major multifunctional perivitellin subunits, immune response, energy metabolism, protein degradation, oxidation-reduction, signaling and binding, transcription and translation, and others. Comparison of gene expression levels between tissues showed that 22 PVF genes were exclusively expressed in albumen gland, the female organ that secretes PVF. Base substitution analysis of PVF and housekeeping genes between P. maculata and its closely related species Pomacea canaliculata showed that the reproductive proteins had a higher mean evolutionary rate. Predicted 3D structures of selected PVF proteins showed that some nonsynonymous substitutions are located at or near the binding regions that may affect protein function. The proteome and sequence divergence analysis revealed a substantial amount of maternal investment in embryonic nutrition and defense, and higher adaptive selective pressure on PVF protein-coding genes when compared with housekeeping genes, providing insight into the adaptations associated with the unusual reproductive strategy in these mollusks. There has been great interest in studying reproduction-related proteins as such studies may not only answer fundamental questions about speciation and evolution, but also solve practical problems of animal infertility and pest outbreak. Our study has demonstrated the effectiveness of an integrated proteomic and transcriptomic approach in understanding the heavy maternal investment of proteins in the eggs of a non-model snail, and how the reproductive proteins may have evolved during the transition from laying underwater eggs to aerial eggs. Copyright © 2017 Elsevier B.V. All rights reserved.

Bioinformatics analysis of transcriptome dynamics during growth in angus cattle longissimus muscle.

PubMed

Moisá, Sonia J; Shike, Daniel W; Graugnard, Daniel E; Rodriguez-Zas, Sandra L; Everts, Robin E; Lewin, Harris A; Faulkner, Dan B; Berger, Larry L; Loor, Juan J

2013-01-01

Transcriptome dynamics in the longissimus muscle (LM) of young Angus cattle were evaluated at 0, 60, 120, and 220 days from early-weaning. Bioinformatic analysis was performed using the dynamic impact approach (DIA) by means of Kyoto Encyclopedia of Genes and Genomes (KEGG) and Database for Annotation, Visualization and Integrated Discovery (DAVID) databases. Between 0 to 120 days (growing phase) most of the highly-impacted pathways (eg, ascorbate and aldarate metabolism, drug metabolism, cytochrome P450 and Retinol metabolism) were inhibited. The phase between 120 to 220 days (finishing phase) was characterized by the most striking differences with 3,784 differentially expressed genes (DEGs). Analysis of those DEGs revealed that the most impacted KEGG canonical pathway was glycosylphosphatidylinositol (GPI)-anchor biosynthesis, which was inhibited. Furthermore, inhibition of calpastatin and activation of tyrosine aminotransferase ubiquitination at 220 days promotes proteasomal degradation, while the concurrent activation of ribosomal proteins promotes protein synthesis. Therefore, the balance of these processes likely results in a steady-state of protein turnover during the finishing phase. Results underscore the importance of transcriptome dynamics in LM during growth.

Identification of Genes Involved in Chemoreception in Plutella xyllostella by Antennal Transcriptome Analysis.

PubMed

Yang, Shiyong; Cao, Depan; Wang, Guirong; Liu, Yang

2017-09-20

Perception of environmental and habitat cues is of significance for insect survival and reproduction. Odor detection in insects is mediated by a number of proteins in antennae such as odorant receptors (ORs), ionotropic receptors (IRs), odorant binding proteins (OBPs), chemosensory proteins (CSPs), sensory neuron membrane proteins (SNMPs) and odorant degrading enzymes. In this study, we sequenced and assembled the adult male and female antennal transcriptomes of a destructive agricultural pest, the diamondback moth Plutella xyllostella. In these transcriptomes, we identified transcripts belonging to 6 chemoreception gene families related to ordor detection, including 54 ORs, 16 IRs, 7 gustatory receptors (GRs), 15 CSPs, 24 OBPs and 2 SNMPs. Semi-quantitative reverse transcription PCR analysis of expression patterns indicated that some of these ORs and IRs have clear sex-biased and tissue-specific expression patterns. Our results lay the foundation for future characterization of the functions of these P. xyllostella chemosensory receptors at the molecular level and development of novel semiochemicals for integrated control of this agricultural pest.

Network and biosignature analysis for the integration of transcriptomic and metabolomic data to characterize leaf senescence process in sunflower.

PubMed

Moschen, Sebastián; Higgins, Janet; Di Rienzo, Julio A; Heinz, Ruth A; Paniego, Norma; Fernandez, Paula

2016-06-06

In recent years, high throughput technologies have led to an increase of datasets from omics disciplines allowing the understanding of the complex regulatory networks associated with biological processes. Leaf senescence is a complex mechanism controlled by multiple genetic and environmental variables, which has a strong impact on crop yield. Transcription factors (TFs) are key proteins in the regulation of gene expression, regulating different signaling pathways; their function is crucial for triggering and/or regulating different aspects of the leaf senescence process. The study of TF interactions and their integration with metabolic profiles under different developmental conditions, especially for a non-model organism such as sunflower, will open new insights into the details of gene regulation of leaf senescence. Weighted Gene Correlation Network Analysis (WGCNA) and BioSignature Discoverer (BioSD, Gnosis Data Analysis, Heraklion, Greece) were used to integrate transcriptomic and metabolomic data. WGCNA allowed the detection of 10 metabolites and 13 TFs whereas BioSD allowed the detection of 1 metabolite and 6 TFs as potential biomarkers. The comparative analysis demonstrated that three transcription factors were detected through both methodologies, highlighting them as potentially robust biomarkers associated with leaf senescence in sunflower. The complementary use of network and BioSignature Discoverer analysis of transcriptomic and metabolomic data provided a useful tool for identifying candidate genes and metabolites which may have a role during the triggering and development of the leaf senescence process. The WGCNA tool allowed us to design and test a hypothetical network in order to infer relationships across selected transcription factor and metabolite candidate biomarkers involved in leaf senescence, whereas BioSignature Discoverer selected transcripts and metabolites which discriminate between different ages of sunflower plants. The methodology presented here would help to elucidate and predict novel networks and potential biomarkers of leaf senescence in sunflower.

Single-cell mass cytometry and transcriptome profiling reveal the impact of graphene on human immune cells.

PubMed

Orecchioni, Marco; Bedognetti, Davide; Newman, Leon; Fuoco, Claudia; Spada, Filomena; Hendrickx, Wouter; Marincola, Francesco M; Sgarrella, Francesco; Rodrigues, Artur Filipe; Ménard-Moyon, Cécilia; Cesareni, Gianni; Kostarelos, Kostas; Bianco, Alberto; Delogu, Lucia G

2017-10-24

Understanding the biomolecular interactions between graphene and human immune cells is a prerequisite for its utilization as a diagnostic or therapeutic tool. To characterize the complex interactions between graphene and immune cells, we propose an integrative analytical pipeline encompassing the evaluation of molecular and cellular parameters. Herein, we use single-cell mass cytometry to dissect the effects of graphene oxide (GO) and GO functionalized with amino groups (GONH 2 ) on 15 immune cell populations, interrogating 30 markers at the single-cell level. Next, the integration of single-cell mass cytometry with genome-wide transcriptome analysis shows that the amine groups reduce the perturbations caused by GO on cell metabolism and increase biocompatibility. Moreover, GONH 2 polarizes T-cell and monocyte activation toward a T helper-1/M1 immune response. This study describes an innovative approach for the analysis of the effects of nanomaterials on distinct immune cells, laying the foundation for the incorporation of single-cell mass cytometry on the experimental pipeline.

A New Combinatorial Optimization Approach for Integrated Feature Selection Using Different Datasets: A Prostate Cancer Transcriptomic Study

PubMed Central

Puthiyedth, Nisha; Riveros, Carlos; Berretta, Regina; Moscato, Pablo

2015-01-01

Background The joint study of multiple datasets has become a common technique for increasing statistical power in detecting biomarkers obtained from smaller studies. The approach generally followed is based on the fact that as the total number of samples increases, we expect to have greater power to detect associations of interest. This methodology has been applied to genome-wide association and transcriptomic studies due to the availability of datasets in the public domain. While this approach is well established in biostatistics, the introduction of new combinatorial optimization models to address this issue has not been explored in depth. In this study, we introduce a new model for the integration of multiple datasets and we show its application in transcriptomics. Methods We propose a new combinatorial optimization problem that addresses the core issue of biomarker detection in integrated datasets. Optimal solutions for this model deliver a feature selection from a panel of prospective biomarkers. The model we propose is a generalised version of the (α,β)-k-Feature Set problem. We illustrate the performance of this new methodology via a challenging meta-analysis task involving six prostate cancer microarray datasets. The results are then compared to the popular RankProd meta-analysis tool and to what can be obtained by analysing the individual datasets by statistical and combinatorial methods alone. Results Application of the integrated method resulted in a more informative signature than the rank-based meta-analysis or individual dataset results, and overcomes problems arising from real world datasets. The set of genes identified is highly significant in the context of prostate cancer. The method used does not rely on homogenisation or transformation of values to a common scale, and at the same time is able to capture markers associated with subgroups of the disease. PMID:26106884

CyanOmics: an integrated database of omics for the model cyanobacterium Synechococcus sp. PCC 7002.

PubMed

Yang, Yaohua; Feng, Jie; Li, Tao; Ge, Feng; Zhao, Jindong

2015-01-01

Cyanobacteria are an important group of organisms that carry out oxygenic photosynthesis and play vital roles in both the carbon and nitrogen cycles of the Earth. The annotated genome of Synechococcus sp. PCC 7002, as an ideal model cyanobacterium, is available. A series of transcriptomic and proteomic studies of Synechococcus sp. PCC 7002 cells grown under different conditions have been reported. However, no database of such integrated omics studies has been constructed. Here we present CyanOmics, a database based on the results of Synechococcus sp. PCC 7002 omics studies. CyanOmics comprises one genomic dataset, 29 transcriptomic datasets and one proteomic dataset and should prove useful for systematic and comprehensive analysis of all those data. Powerful browsing and searching tools are integrated to help users directly access information of interest with enhanced visualization of the analytical results. Furthermore, Blast is included for sequence-based similarity searching and Cluster 3.0, as well as the R hclust function is provided for cluster analyses, to increase CyanOmics's usefulness. To the best of our knowledge, it is the first integrated omics analysis database for cyanobacteria. This database should further understanding of the transcriptional patterns, and proteomic profiling of Synechococcus sp. PCC 7002 and other cyanobacteria. Additionally, the entire database framework is applicable to any sequenced prokaryotic genome and could be applied to other integrated omics analysis projects. Database URL: http://lag.ihb.ac.cn/cyanomics. © The Author(s) 2015. Published by Oxford University Press.

Gene expression profiling of immunomagnetically separated cells directly from stabilized whole blood for multicenter clinical trials

PubMed Central

2014-01-01

Background Clinically useful biomarkers for patient stratification and monitoring of disease progression and drug response are in big demand in drug development and for addressing potential safety concerns. Many diseases influence the frequency and phenotype of cells found in the peripheral blood and the transcriptome of blood cells. Changes in cell type composition influence whole blood gene expression analysis results and thus the discovery of true transcript level changes remains a challenge. We propose a robust and reproducible procedure, which includes whole transcriptome gene expression profiling of major subsets of immune cell cells directly sorted from whole blood. Methods Target cells were enriched using magnetic microbeads and an autoMACS® Pro Separator (Miltenyi Biotec). Flow cytometric analysis for purity was performed before and after magnetic cell sorting. Total RNA was hybridized on HGU133 Plus 2.0 expression microarrays (Affymetrix, USA). CEL files signal intensity values were condensed using RMA and a custom CDF file (EntrezGene-based). Results Positive selection by use of MACS® Technology coupled to transcriptomics was assessed for eight different peripheral blood cell types, CD14+ monocytes, CD3+, CD4+, or CD8+ T cells, CD15+ granulocytes, CD19+ B cells, CD56+ NK cells, and CD45+ pan leukocytes. RNA quality from enriched cells was above a RIN of eight. GeneChip analysis confirmed cell type specific transcriptome profiles. Storing whole blood collected in an EDTA Vacutainer® tube at 4°C followed by MACS does not activate sorted cells. Gene expression analysis supports cell enrichment measurements by MACS. Conclusions The proposed workflow generates reproducible cell-type specific transcriptome data which can be translated to clinical settings and used to identify clinically relevant gene expression biomarkers from whole blood samples. This procedure enables the integration of transcriptomics of relevant immune cell subsets sorted directly from whole blood in clinical trial protocols. PMID:25984272

A regulation probability model-based meta-analysis of multiple transcriptomics data sets for cancer biomarker identification.

PubMed

Xie, Xin-Ping; Xie, Yu-Feng; Wang, Hong-Qiang

2017-08-23

Large-scale accumulation of omics data poses a pressing challenge of integrative analysis of multiple data sets in bioinformatics. An open question of such integrative analysis is how to pinpoint consistent but subtle gene activity patterns across studies. Study heterogeneity needs to be addressed carefully for this goal. This paper proposes a regulation probability model-based meta-analysis, jGRP, for identifying differentially expressed genes (DEGs). The method integrates multiple transcriptomics data sets in a gene regulatory space instead of in a gene expression space, which makes it easy to capture and manage data heterogeneity across studies from different laboratories or platforms. Specifically, we transform gene expression profiles into a united gene regulation profile across studies by mathematically defining two gene regulation events between two conditions and estimating their occurring probabilities in a sample. Finally, a novel differential expression statistic is established based on the gene regulation profiles, realizing accurate and flexible identification of DEGs in gene regulation space. We evaluated the proposed method on simulation data and real-world cancer datasets and showed the effectiveness and efficiency of jGRP in identifying DEGs identification in the context of meta-analysis. Data heterogeneity largely influences the performance of meta-analysis of DEGs identification. Existing different meta-analysis methods were revealed to exhibit very different degrees of sensitivity to study heterogeneity. The proposed method, jGRP, can be a standalone tool due to its united framework and controllable way to deal with study heterogeneity.

An Integrated Proteomics/Transcriptomics Approach Points to Oxygen as the Main Electron Sink for Methanol Metabolism in Methylotenera mobilis▿†

PubMed Central

Beck, David A. C.; Hendrickson, Erik L.; Vorobev, Alexey; Wang, Tiansong; Lim, Sujung; Kalyuzhnaya, Marina G.; Lidstrom, Mary E.; Hackett, Murray; Chistoserdova, Ludmila

2011-01-01

Methylotenera species, unlike their close relatives in the genera Methylophilus, Methylobacillus, and Methylovorus, neither exhibit the activity of methanol dehydrogenase nor possess mxaFI genes encoding this enzyme, yet they are able to grow on methanol. In this work, we integrated a genome-wide proteomics approach, shotgun proteomics, and a genome-wide transcriptomics approach, shotgun transcriptome sequencing (RNA-seq), of Methylotenera mobilis JLW8 to identify genes and enzymes potentially involved in methanol oxidation, with special attention to alternative nitrogen sources, to address the question of whether nitrate could play a role as an electron acceptor in place of oxygen. Both proteomics and transcriptomics identified a limited number of genes and enzymes specifically responding to methanol. This set includes genes involved in oxidative stress response systems, a number of oxidoreductases, including XoxF-type alcohol dehydrogenases, a type II secretion system, and proteins without a predicted function. Nitrate stimulated expression of some genes in assimilatory nitrate reduction and denitrification pathways, while ammonium downregulated some of the nitrogen metabolism genes. However, none of these genes appeared to respond to methanol, which suggests that oxygen may be the main electron sink during growth on methanol. This study identifies initial targets for future focused physiological studies, including mutant analysis, which will provide further details into this novel process. PMID:21764938

An Analysis of the Sensitivity of Proteogenomic Mapping of Somatic Mutations and Novel Splicing Events in Cancer.

PubMed

Ruggles, Kelly V; Tang, Zuojian; Wang, Xuya; Grover, Himanshu; Askenazi, Manor; Teubl, Jennifer; Cao, Song; McLellan, Michael D; Clauser, Karl R; Tabb, David L; Mertins, Philipp; Slebos, Robbert; Erdmann-Gilmore, Petra; Li, Shunqiang; Gunawardena, Harsha P; Xie, Ling; Liu, Tao; Zhou, Jian-Ying; Sun, Shisheng; Hoadley, Katherine A; Perou, Charles M; Chen, Xian; Davies, Sherri R; Maher, Christopher A; Kinsinger, Christopher R; Rodland, Karen D; Zhang, Hui; Zhang, Zhen; Ding, Li; Townsend, R Reid; Rodriguez, Henry; Chan, Daniel; Smith, Richard D; Liebler, Daniel C; Carr, Steven A; Payne, Samuel; Ellis, Matthew J; Fenyő, David

2016-03-01

Improvements in mass spectrometry (MS)-based peptide sequencing provide a new opportunity to determine whether polymorphisms, mutations, and splice variants identified in cancer cells are translated. Herein, we apply a proteogenomic data integration tool (QUILTS) to illustrate protein variant discovery using whole genome, whole transcriptome, and global proteome datasets generated from a pair of luminal and basal-like breast-cancer-patient-derived xenografts (PDX). The sensitivity of proteogenomic analysis for singe nucleotide variant (SNV) expression and novel splice junction (NSJ) detection was probed using multiple MS/MS sample process replicates defined here as an independent tandem MS experiment using identical sample material. Despite analysis of over 30 sample process replicates, only about 10% of SNVs (somatic and germline) detected by both DNA and RNA sequencing were observed as peptides. An even smaller proportion of peptides corresponding to NSJ observed by RNA sequencing were detected (<0.1%). Peptides mapping to DNA-detected SNVs without a detectable mRNA transcript were also observed, suggesting that transcriptome coverage was incomplete (∼80%). In contrast to germline variants, somatic variants were less likely to be detected at the peptide level in the basal-like tumor than in the luminal tumor, raising the possibility of differential translation or protein degradation effects. In conclusion, this large-scale proteogenomic integration allowed us to determine the degree to which mutations are translated and identify gaps in sequence coverage, thereby benchmarking current technology and progress toward whole cancer proteome and transcriptome analysis. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

Simultaneous transcriptome analysis of Colletotrichum gloeosporioides and tomato fruit pathosystem reveals novel fungal pathogenicity and fruit defense strategies.

PubMed

Alkan, Noam; Friedlander, Gilgi; Ment, Dana; Prusky, Dov; Fluhr, Robert

2015-01-01

The fungus Colletotrichum gloeosporioides breaches the fruit cuticle but remains quiescent until fruit ripening signals a switch to necrotrophy, culminating in devastating anthracnose disease. There is a need to understand the distinct fungal arms strategy and the simultaneous fruit response. Transcriptome analysis of fungal-fruit interactions was carried out concurrently in the appressoria, quiescent and necrotrophic stages. Conidia germinating on unripe fruit cuticle showed stage-specific transcription that was accompanied by massive fruit defense responses. The subsequent quiescent stage showed the development of dendritic-like structures and swollen hyphae within the fruit epidermis. The quiescent fungal transcriptome was characterized by activation of chromatin remodeling genes and unsuspected environmental alkalization. Fruit response was portrayed by continued highly integrated massive up-regulation of defense genes. During cuticle infection of green or ripe fruit, fungi recapitulate the same developmental stages but with differing quiescent time spans. The necrotrophic stage showed a dramatic shift in fungal metabolism and up-regulation of pathogenicity factors. Fruit response to necrotrophy showed activation of the salicylic acid pathway, climaxing in cell death. Transcriptome analysis of C. gloeosporioides infection of fruit reveals its distinct stage-specific lifestyle and the concurrent changing fruit response, deepening our perception of the unfolding fungal-fruit arms and defenses race. © 2014 The Authors. New Phytologist © 2014 New Phytologist Trust.

Strategic and Operational Plan for Integrating Transcriptomics ...

EPA Pesticide Factsheets

Plans for incorporating high throughput transcriptomics into the current high throughput screening activities at NCCT; the details are in the attached slide presentation presentation on plans for incorporating high throughput transcriptomics into the current high throughput screening activities at NCCT, given at the OECD meeting on June 23, 2016

A global approach to analysis and interpretation of metabolic data for plant natural product discovery.

PubMed

Hur, Manhoi; Campbell, Alexis Ann; Almeida-de-Macedo, Marcia; Li, Ling; Ransom, Nick; Jose, Adarsh; Crispin, Matt; Nikolau, Basil J; Wurtele, Eve Syrkin

2013-04-01

Discovering molecular components and their functionality is key to the development of hypotheses concerning the organization and regulation of metabolic networks. The iterative experimental testing of such hypotheses is the trajectory that can ultimately enable accurate computational modelling and prediction of metabolic outcomes. This information can be particularly important for understanding the biology of natural products, whose metabolism itself is often only poorly defined. Here, we describe factors that must be in place to optimize the use of metabolomics in predictive biology. A key to achieving this vision is a collection of accurate time-resolved and spatially defined metabolite abundance data and associated metadata. One formidable challenge associated with metabolite profiling is the complexity and analytical limits associated with comprehensively determining the metabolome of an organism. Further, for metabolomics data to be efficiently used by the research community, it must be curated in publicly available metabolomics databases. Such databases require clear, consistent formats, easy access to data and metadata, data download, and accessible computational tools to integrate genome system-scale datasets. Although transcriptomics and proteomics integrate the linear predictive power of the genome, the metabolome represents the nonlinear, final biochemical products of the genome, which results from the intricate system(s) that regulate genome expression. For example, the relationship of metabolomics data to the metabolic network is confounded by redundant connections between metabolites and gene-products. However, connections among metabolites are predictable through the rules of chemistry. Therefore, enhancing the ability to integrate the metabolome with anchor-points in the transcriptome and proteome will enhance the predictive power of genomics data. We detail a public database repository for metabolomics, tools and approaches for statistical analysis of metabolomics data, and methods for integrating these datasets with transcriptomic data to create hypotheses concerning specialized metabolisms that generate the diversity in natural product chemistry. We discuss the importance of close collaborations among biologists, chemists, computer scientists and statisticians throughout the development of such integrated metabolism-centric databases and software.

A global approach to analysis and interpretation of metabolic data for plant natural product discovery†

PubMed Central

Hur, Manhoi; Campbell, Alexis Ann; Almeida-de-Macedo, Marcia; Li, Ling; Ransom, Nick; Jose, Adarsh; Crispin, Matt; Nikolau, Basil J.

2013-01-01

Discovering molecular components and their functionality is key to the development of hypotheses concerning the organization and regulation of metabolic networks. The iterative experimental testing of such hypotheses is the trajectory that can ultimately enable accurate computational modelling and prediction of metabolic outcomes. This information can be particularly important for understanding the biology of natural products, whose metabolism itself is often only poorly defined. Here, we describe factors that must be in place to optimize the use of metabolomics in predictive biology. A key to achieving this vision is a collection of accurate time-resolved and spatially defined metabolite abundance data and associated metadata. One formidable challenge associated with metabolite profiling is the complexity and analytical limits associated with comprehensively determining the metabolome of an organism. Further, for metabolomics data to be efficiently used by the research community, it must be curated in publically available metabolomics databases. Such databases require clear, consistent formats, easy access to data and metadata, data download, and accessible computational tools to integrate genome system-scale datasets. Although transcriptomics and proteomics integrate the linear predictive power of the genome, the metabolome represents the nonlinear, final biochemical products of the genome, which results from the intricate system(s) that regulate genome expression. For example, the relationship of metabolomics data to the metabolic network is confounded by redundant connections between metabolites and gene-products. However, connections among metabolites are predictable through the rules of chemistry. Therefore, enhancing the ability to integrate the metabolome with anchor-points in the transcriptome and proteome will enhance the predictive power of genomics data. We detail a public database repository for metabolomics, tools and approaches for statistical analysis of metabolomics data, and methods for integrating these dataset with transcriptomic data to create hypotheses concerning specialized metabolism that generates the diversity in natural product chemistry. We discuss the importance of close collaborations among biologists, chemists, computer scientists and statisticians throughout the development of such integrated metabolism-centric databases and software. PMID:23447050

expVIP: a Customizable RNA-seq Data Analysis and Visualization Platform1[OPEN

PubMed Central

2016-01-01

The majority of transcriptome sequencing (RNA-seq) expression studies in plants remain underutilized and inaccessible due to the use of disparate transcriptome references and the lack of skills and resources to analyze and visualize these data. We have developed expVIP, an expression visualization and integration platform, which allows easy analysis of RNA-seq data combined with an intuitive and interactive interface. Users can analyze public and user-specified data sets with minimal bioinformatics knowledge using the expVIP virtual machine. This generates a custom Web browser to visualize, sort, and filter the RNA-seq data and provides outputs for differential gene expression analysis. We demonstrate expVIP’s suitability for polyploid crops and evaluate its performance across a range of biologically relevant scenarios. To exemplify its use in crop research, we developed a flexible wheat (Triticum aestivum) expression browser (www.wheat-expression.com) that can be expanded with user-generated data in a local virtual machine environment. The open-access expVIP platform will facilitate the analysis of gene expression data from a wide variety of species by enabling the easy integration, visualization, and comparison of RNA-seq data across experiments. PMID:26869702

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ruggles, Kelly V.; Tang, Zuojian; Wang, Xuya

Improvements in mass spectrometry (MS)-based peptide sequencing provide a new opportunity to determine whether polymorphisms, mutations and splice variants identified in cancer cells are translated. Herein we therefore describe a proteogenomic data integration tool (QUILTS) and illustrate its application to whole genome, transcriptome and global MS peptide sequence datasets generated from a pair of luminal and basal-like breast cancer patient derived xenografts (PDX). The sensitivity of proteogenomic analysis for singe nucleotide variant (SNV) expression and novel splice junction (NSJ) detection was probed using multiple MS/MS process replicates. Despite over thirty sample replicates, only about 10% of all SNV (somatic andmore » germline) were detected by both DNA and RNA sequencing were observed as peptides. An even smaller proportion of peptides corresponding to NSJ observed by RNA sequencing were detected (<0.1%). Peptides mapping to DNA-detected SNV without a detectable mRNA transcript were also observed demonstrating the transcriptome coverage was also incomplete (~80%). In contrast to germ-line variants, somatic variants were less likely to be detected at the peptide level in the basal-like tumor than the luminal tumor raising the possibility of differential translation or protein degradation effects. In conclusion, the QUILTS program integrates DNA, RNA and peptide sequencing to assess the degree to which somatic mutations are translated and therefore biologically active. By identifying gaps in sequence coverage QUILTS benchmarks current technology and assesses progress towards whole cancer proteome and transcriptome analysis.« less

The genomic and transcriptomic architecture of 2,000 breast tumours reveals novel subgroups

PubMed Central

Curtis, Christina; Shah, Sohrab P.; Chin, Suet-Feung; Turashvili, Gulisa; Rueda, Oscar M.; Dunning, Mark J.; Speed, Doug; Lynch, Andy G.; Samarajiwa, Shamith; Yuan, Yinyin; Gräf, Stefan; Ha, Gavin; Haffari, Gholamreza; Bashashati, Ali; Russell, Roslin; McKinney, Steven; Langerød, Anita; Green, Andrew; Provenzano, Elena; Wishart, Gordon; Pinder, Sarah; Watson, Peter; Markowetz, Florian; Murphy, Leigh; Ellis, Ian; Purushotham, Arnie; Børresen-Dale, Anne-Lise; Brenton, James D.; Tavaré, Simon; Caldas, Carlos; Aparicio, Samuel

2012-01-01

The elucidation of breast cancer subgroups and their molecular drivers requires integrated views of the genome and transcriptome from representative numbers of patients. We present an integrated analysis of copy number and gene expression in a discovery and validation set of 997 and 995 primary breast tumours, respectively, with long-term clinical follow-up. Inherited variants (copy number variants and single nucleotide polymorphisms) and acquired somatic copy number aberrations (CNAs) were associated with expression in ~40% of genes, with the landscape dominated by cis- and trans-acting CNAs. By delineating expression outlier genes driven in cis by CNAs, we identified putative cancer genes, including deletions in PPP2R2A, MTAP and MAP2K4. Unsupervised analysis of paired DNA–RNA profiles revealed novel subgroups with distinct clinical outcomes, which reproduced in the validation cohort. These include a high-risk, oestrogen-receptor-positive 11q13/14 cis-acting subgroup and a favourable prognosis subgroup devoid of CNAs. Trans-acting aberration hotspots were found to modulate subgroup-specific gene networks, including a TCR deletion-mediated adaptive immune response in the ‘CNA-devoid’ subgroup and a basal-specific chromosome 5 deletion-associated mitotic network. Our results provide a novel molecular stratification of the breast cancer population, derived from the impact of somatic CNAs on the transcriptome. PMID:22522925

Integrated network analysis identifies fight-club nodes as a class of hubs encompassing key putative switch genes that induce major transcriptome reprogramming during grapevine development.

PubMed

Palumbo, Maria Concetta; Zenoni, Sara; Fasoli, Marianna; Massonnet, Mélanie; Farina, Lorenzo; Castiglione, Filippo; Pezzotti, Mario; Paci, Paola

2014-12-01

We developed an approach that integrates different network-based methods to analyze the correlation network arising from large-scale gene expression data. By studying grapevine (Vitis vinifera) and tomato (Solanum lycopersicum) gene expression atlases and a grapevine berry transcriptomic data set during the transition from immature to mature growth, we identified a category named "fight-club hubs" characterized by a marked negative correlation with the expression profiles of neighboring genes in the network. A special subset named "switch genes" was identified, with the additional property of many significant negative correlations outside their own group in the network. Switch genes are involved in multiple processes and include transcription factors that may be considered master regulators of the previously reported transcriptome remodeling that marks the developmental shift from immature to mature growth. All switch genes, expressed at low levels in vegetative/green tissues, showed a significant increase in mature/woody organs, suggesting a potential regulatory role during the developmental transition. Finally, our analysis of tomato gene expression data sets showed that wild-type switch genes are downregulated in ripening-deficient mutants. The identification of known master regulators of tomato fruit maturation suggests our method is suitable for the detection of key regulators of organ development in different fleshy fruit crops. © 2014 American Society of Plant Biologists. All rights reserved.

Integrated Network Analysis Identifies Fight-Club Nodes as a Class of Hubs Encompassing Key Putative Switch Genes That Induce Major Transcriptome Reprogramming during Grapevine Development[W][OPEN

PubMed Central

Palumbo, Maria Concetta; Zenoni, Sara; Fasoli, Marianna; Massonnet, Mélanie; Farina, Lorenzo; Castiglione, Filippo; Pezzotti, Mario; Paci, Paola

2014-01-01

We developed an approach that integrates different network-based methods to analyze the correlation network arising from large-scale gene expression data. By studying grapevine (Vitis vinifera) and tomato (Solanum lycopersicum) gene expression atlases and a grapevine berry transcriptomic data set during the transition from immature to mature growth, we identified a category named “fight-club hubs” characterized by a marked negative correlation with the expression profiles of neighboring genes in the network. A special subset named “switch genes” was identified, with the additional property of many significant negative correlations outside their own group in the network. Switch genes are involved in multiple processes and include transcription factors that may be considered master regulators of the previously reported transcriptome remodeling that marks the developmental shift from immature to mature growth. All switch genes, expressed at low levels in vegetative/green tissues, showed a significant increase in mature/woody organs, suggesting a potential regulatory role during the developmental transition. Finally, our analysis of tomato gene expression data sets showed that wild-type switch genes are downregulated in ripening-deficient mutants. The identification of known master regulators of tomato fruit maturation suggests our method is suitable for the detection of key regulators of organ development in different fleshy fruit crops. PMID:25490918

Transcriptomic Studies of Malaria: a Paradigm for Investigation of Systemic Host-Pathogen Interactions

PubMed Central

2018-01-01

SUMMARY Transcriptomics, the analysis of genome-wide RNA expression, is a common approach to investigate host and pathogen processes in infectious diseases. Technical and bioinformatic advances have permitted increasingly thorough analyses of the association of RNA expression with fundamental biology, immunity, pathogenesis, diagnosis, and prognosis. Transcriptomic approaches can now be used to realize a previously unattainable goal, the simultaneous study of RNA expression in host and pathogen, in order to better understand their interactions. This exciting prospect is not without challenges, especially as focus moves from interactions in vitro under tightly controlled conditions to tissue- and systems-level interactions in animal models and natural and experimental infections in humans. Here we review the contribution of transcriptomic studies to the understanding of malaria, a parasitic disease which has exerted a major influence on human evolution and continues to cause a huge global burden of disease. We consider malaria a paradigm for the transcriptomic assessment of systemic host-pathogen interactions in humans, because much of the direct host-pathogen interaction occurs within the blood, a readily sampled compartment of the body. We illustrate lessons learned from transcriptomic studies of malaria and how these lessons may guide studies of host-pathogen interactions in other infectious diseases. We propose that the potential of transcriptomic studies to improve the understanding of malaria as a disease remains partly untapped because of limitations in study design rather than as a consequence of technological constraints. Further advances will require the integration of transcriptomic data with analytical approaches from other scientific disciplines, including epidemiology and mathematical modeling. PMID:29695497

Transcriptomic Studies of Malaria: a Paradigm for Investigation of Systemic Host-Pathogen Interactions.

PubMed

Lee, Hyun Jae; Georgiadou, Athina; Otto, Thomas D; Levin, Michael; Coin, Lachlan J; Conway, David J; Cunnington, Aubrey J

2018-06-01

Transcriptomics, the analysis of genome-wide RNA expression, is a common approach to investigate host and pathogen processes in infectious diseases. Technical and bioinformatic advances have permitted increasingly thorough analyses of the association of RNA expression with fundamental biology, immunity, pathogenesis, diagnosis, and prognosis. Transcriptomic approaches can now be used to realize a previously unattainable goal, the simultaneous study of RNA expression in host and pathogen, in order to better understand their interactions. This exciting prospect is not without challenges, especially as focus moves from interactions in vitro under tightly controlled conditions to tissue- and systems-level interactions in animal models and natural and experimental infections in humans. Here we review the contribution of transcriptomic studies to the understanding of malaria, a parasitic disease which has exerted a major influence on human evolution and continues to cause a huge global burden of disease. We consider malaria a paradigm for the transcriptomic assessment of systemic host-pathogen interactions in humans, because much of the direct host-pathogen interaction occurs within the blood, a readily sampled compartment of the body. We illustrate lessons learned from transcriptomic studies of malaria and how these lessons may guide studies of host-pathogen interactions in other infectious diseases. We propose that the potential of transcriptomic studies to improve the understanding of malaria as a disease remains partly untapped because of limitations in study design rather than as a consequence of technological constraints. Further advances will require the integration of transcriptomic data with analytical approaches from other scientific disciplines, including epidemiology and mathematical modeling. Copyright © 2018 Lee et al.

Integration analysis of quantitative proteomics and transcriptomics data identifies potential targets of frizzled-8 protein-related antiproliferative factor in vivo.

PubMed

Yang, Wei; Kim, Yongsoo; Kim, Taek-Kyun; Keay, Susan K; Kim, Kwang Pyo; Steen, Hanno; Freeman, Michael R; Hwang, Daehee; Kim, Jayoung

2012-12-01

What's known on the subject? and What does the study add? Interstitial cystitis (IC) is a prevalent and debilitating pelvic disorder generally accompanied by chronic pain combined with chronic urinating problems. Over one million Americans are affected, especially middle-aged women. However, its aetiology or mechanism remains unclear. No efficient drug has been provided to patients. Several urinary biomarker candidates have been identified for IC; among the most promising is antiproliferative factor (APF), whose biological activity is detectable in urine specimens from >94% of patients with both ulcerative and non-ulcerative IC. The present study identified several important mediators of the effect of APF on bladder cell physiology, suggesting several candidate drug targets against IC. In an attempt to identify potential proteins and genes regulated by APF in vivo, and to possibly expand the APF-regulated network identified by stable isotope labelling by amino acids in cell culture (SILAC), we performed an integration analysis of our own SILAC data and the microarray data of Gamper et al. (2009) BMC Genomics 10: 199. Notably, two of the proteins (i.e. MAPKSP1 and GSPT1) that are down-regulated by APF are involved in the activation of mTORC1, suggesting that the mammalian target of rapamycin (mTOR) pathway is potentially a critical pathway regulated by APF in vivo. Several components of the mTOR pathway are currently being studied as potential therapeutic targets in other diseases. Our analysis suggests that this pathway might also be relevant in the design of diagnostic tools and medications targeting IC. • To enhance our understanding of the interstitial cystitis urine biomarker antiproliferative factor (APF), as well as interstitial cystitis biology more generally at the systems level, we reanalyzed recently published large-scale quantitative proteomics and in vivo transcriptomics data sets using an integration analysis tool that we have developed. • To identify more differentially expressed genes with a lower false discovery rate from a previously published microarray data set, an integrative hypothesis-testing statistical approach was applied. • For validation experiments, expression and phosphorylation levels of select proteins were evaluated by western blotting. • Integration analysis of this transcriptomics data set with our own quantitative proteomics data set identified 10 genes that are potentially regulated by APF in vivo from 4140 differentially expressed genes identified with a false discovery rate of 1%. • Of these, five (i.e. JUP, MAPKSP1, GSPT1, PTGS2/COX-2 and XPOT) were found to be prominent after network modelling of the common genes identified in the proteomics and microarray studies. • This molecular signature reflects the biological processes of cell adhesion, cell proliferation and inflammation, which is consistent with the known physiological effects of APF. • Lastly, we found the mammalian target of rapamycin pathway was down-regulated in response to APF. • This unbiased integration analysis of in vitro quantitative proteomics data with in vivo quantitative transcriptomics data led to the identification of potential downstream mediators of the APF signal transduction pathway. © 2012 THE AUTHORS. BJU INTERNATIONAL © 2012 BJU INTERNATIONAL.

Integrative analysis of transcriptomic and metabolomic data via sparse canonical correlation analysis with incorporation of biological information.

PubMed

Safo, Sandra E; Li, Shuzhao; Long, Qi

2018-03-01

Integrative analysis of high dimensional omics data is becoming increasingly popular. At the same time, incorporating known functional relationships among variables in analysis of omics data has been shown to help elucidate underlying mechanisms for complex diseases. In this article, our goal is to assess association between transcriptomic and metabolomic data from a Predictive Health Institute (PHI) study that includes healthy adults at a high risk of developing cardiovascular diseases. Adopting a strategy that is both data-driven and knowledge-based, we develop statistical methods for sparse canonical correlation analysis (CCA) with incorporation of known biological information. Our proposed methods use prior network structural information among genes and among metabolites to guide selection of relevant genes and metabolites in sparse CCA, providing insight on the molecular underpinning of cardiovascular disease. Our simulations demonstrate that the structured sparse CCA methods outperform several existing sparse CCA methods in selecting relevant genes and metabolites when structural information is informative and are robust to mis-specified structural information. Our analysis of the PHI study reveals that a number of gene and metabolic pathways including some known to be associated with cardiovascular diseases are enriched in the set of genes and metabolites selected by our proposed approach. © 2017, The International Biometric Society.

Large-scale atlas of microarray data reveals biological landscape of gene expression in Arabidopsis

USDA-ARS?s Scientific Manuscript database

Transcriptome datasets from thousands of samples of the model plant Arabidopsis thaliana have been collectively generated by multiple individual labs. Although integration and meta-analysis of these samples has become routine in the plant research community, it is often hampered by the lack of metad...

Integrated genomic and transcriptomic analysis reveals mycoparasitism as the ancestoral life style of Trichoderma

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kubicek, Christian P.; Herrera-Estrella, Alfredo; Seidl, Verena

2011-04-29

Mycoparasitism, a lifestyle where one fungus is parasitic on another fungus has special relevance when the prey is a plant pathogen, providing a strategy for biological control of pests for plant protection. Probably, the most studied biocontrol agents are species of the genus Hypocrea/Trichoderma.

Harnessing pain heterogeneity and RNA transcriptome to identify blood-based pain biomarkers: a novel correlational study design and bioinformatics approach in a graded chronic constriction injury model.

PubMed

Grace, Peter M; Hurley, Daniel; Barratt, Daniel T; Tsykin, Anna; Watkins, Linda R; Rolan, Paul E; Hutchinson, Mark R

2012-09-01

A quantitative, peripherally accessible biomarker for neuropathic pain has great potential to improve clinical outcomes. Based on the premise that peripheral and central immunity contribute to neuropathic pain mechanisms, we hypothesized that biomarkers could be identified from the whole blood of adult male rats, by integrating graded chronic constriction injury (CCI), ipsilateral lumbar dorsal quadrant (iLDQ) and whole blood transcriptomes, and pathway analysis with pain behavior. Correlational bioinformatics identified a range of putative biomarker genes for allodynia intensity, many encoding for proteins with a recognized role in immune/nociceptive mechanisms. A selection of these genes was validated in a separate replication study. Pathway analysis of the iLDQ transcriptome identified Fcγ and Fcε signaling pathways, among others. This study is the first to employ the whole blood transcriptome to identify pain biomarker panels. The novel correlational bioinformatics, developed here, selected such putative biomarkers based on a correlation with pain behavior and formation of signaling pathways with iLDQ genes. Future studies may demonstrate the predictive ability of these biomarker genes across other models and additional variables. © 2012 The Authors. Journal of Neurochemistry © 2012 International Society for Neurochemistry.

Discovery and Annotation of Plant Endogenous Target Mimicry Sequences from Public Transcriptome Libraries: A Case Study of Prunus persica.

PubMed

Karakülah, Gökhan

2017-06-28

Novel transcript discovery through RNA sequencing has substantially improved our understanding of the transcriptome dynamics of biological systems. Endogenous target mimicry (eTM) transcripts, a novel class of regulatory molecules, bind to their target microRNAs (miRNAs) by base pairing and block their biological activity. The objective of this study was to provide a computational analysis framework for the prediction of putative eTM sequences in plants, and as an example, to discover previously un-annotated eTMs in Prunus persica (peach) transcriptome. Therefore, two public peach transcriptome libraries downloaded from Sequence Read Archive (SRA) and a previously published set of long non-coding RNAs (lncRNAs) were investigated with multi-step analysis pipeline, and 44 putative eTMs were found. Additionally, an eTM-miRNA-mRNA regulatory network module associated with peach fruit organ development was built via integration of the miRNA target information and predicted eTM-miRNA interactions. My findings suggest that one of the most widely expressed miRNA families among diverse plant species, miR156, might be potentially sponged by seven putative eTMs. Besides, the study indicates eTMs potentially play roles in the regulation of development processes in peach fruit via targeting specific miRNAs. In conclusion, by following the step-by step instructions provided in this study, novel eTMs can be identified and annotated effectively in public plant transcriptome libraries.

Integration of Transcriptome, Proteome and Metabolism Data Reveals the Alkaloids Biosynthesis in Macleaya cordata and Macleaya microcarpa

PubMed Central

Liu, Fuqing; Huang, Peng; Zhu, Pengcheng; Chen, Jinjun; Shi, Mingming; Guo, Fang; Cheng, Pi; Zeng, Jing; Liao, Yifang; Gong, Jing; Zhang, Hong-Mei; Wang, Depeng; Guo, An-Yuan; Xiong, Xingyao

2013-01-01

Background The Macleaya spp., including Macleaya cordata and Macleaya microcarpa, are traditional anti-virus, inflammation eliminating, and insecticide herb medicines for their isoquinoline alkaloids. They are also known as the basis of the popular natural animal food addictive in Europe. However, few studies especially at genomics level were conducted on them. Hence, we performed the Macleaya spp. transcriptome and integrated it with iTRAQ proteome analysis in order to identify potential genes involved in alkaloids biosynthesis. Methodology and Principal Findings We elaborately designed the transcriptome, proteome and metabolism profiling for 10 samples of both species to explore their alkaloids biosynthesis. From the transcriptome data, we obtained 69367 and 78255 unigenes for M. cordata and M. microcarpa, in which about two thirds of them were similar to sequences in public databases. By metabolism profiling, reverse patterns for alkaloids sanguinarine, chelerythrine, protopine, and allocryptopine were observed in different organs of two species. We characterized the expressions of enzymes in alkaloid biosynthesis pathways. We also identified more than 1000 proteins from iTRAQ proteome data. Our results strongly suggest that the root maybe the organ for major alkaloids biosynthesis of Macleaya spp. Except for biosynthesis, the alkaloids storage and transport were also important for their accumulation. The ultrastructure of laticifers by SEM helps us to prove the alkaloids maybe accumulated in the mature roots. Conclusions/Significance To our knowledge this is the first study to elucidate the genetic makeup of Macleaya spp. This work provides clues to the identification of the potential modulate genes involved in alkaloids biosynthesis in Macleaya spp., and sheds light on researches for non-model medicinal plants by integrating different high-throughput technologies. PMID:23326424

UniVIO: A Multiple Omics Database with Hormonome and Transcriptome Data from Rice

PubMed Central

Sakurai, Tetsuya; Sakakibara, Hitoshi

2013-01-01

Plant hormones play important roles as signaling molecules in the regulation of growth and development by controlling the expression of downstream genes. Since the hormone signaling system represents a complex network involving functional cross-talk through the mutual regulation of signaling and metabolism, a comprehensive and integrative analysis of plant hormone concentrations and gene expression is important for a deeper understanding of hormone actions. We have developed a database named Uniformed Viewer for Integrated Omics (UniVIO: http://univio.psc.riken.jp/), which displays hormone-metabolome (hormonome) and transcriptome data in a single formatted (uniformed) heat map. At the present time, hormonome and transcriptome data obtained from 14 organ parts of rice plants at the reproductive stage and seedling shoots of three gibberellin signaling mutants are included in the database. The hormone concentration and gene expression data can be searched by substance name, probe ID, gene locus ID or gene description. A correlation search function has been implemented to enable users to obtain information of correlated substance accumulation and gene expression. In the correlation search, calculation method, range of correlation coefficient and plant samples can be selected freely. PMID:23314752

Integrated Transcriptomic and Epigenomic Analysis of Primary Human Lung Epithelial Cell Differentiation

PubMed Central

Marconett, Crystal N.; Zhou, Beiyun; Rieger, Megan E.; Selamat, Suhaida A.; Dubourd, Mickael; Fang, Xiaohui; Lynch, Sean K.; Stueve, Theresa Ryan; Siegmund, Kimberly D.; Berman, Benjamin P.

2013-01-01

Elucidation of the epigenetic basis for cell-type specific gene regulation is key to gaining a full understanding of how the distinct phenotypes of differentiated cells are achieved and maintained. Here we examined how epigenetic changes are integrated with transcriptional activation to determine cell phenotype during differentiation. We performed epigenomic profiling in conjunction with transcriptomic profiling using in vitro differentiation of human primary alveolar epithelial cells (AEC). This model recapitulates an in vivo process in which AEC transition from one differentiated cell type to another during regeneration following lung injury. Interrogation of histone marks over time revealed enrichment of specific transcription factor binding motifs within regions of changing chromatin structure. Cross-referencing of these motifs with pathways showing transcriptional changes revealed known regulatory pathways of distal alveolar differentiation, such as the WNT and transforming growth factor beta (TGFB) pathways, and putative novel regulators of adult AEC differentiation including hepatocyte nuclear factor 4 alpha (HNF4A), and the retinoid X receptor (RXR) signaling pathways. Inhibition of the RXR pathway confirmed its functional relevance for alveolar differentiation. Our incorporation of epigenetic data allowed specific identification of transcription factors that are potential direct upstream regulators of the differentiation process, demonstrating the power of this approach. Integration of epigenomic data with transcriptomic profiling has broad application for the identification of regulatory pathways in other models of differentiation. PMID:23818859

SPARTA: Simple Program for Automated reference-based bacterial RNA-seq Transcriptome Analysis.

PubMed

Johnson, Benjamin K; Scholz, Matthew B; Teal, Tracy K; Abramovitch, Robert B

2016-02-04

Many tools exist in the analysis of bacterial RNA sequencing (RNA-seq) transcriptional profiling experiments to identify differentially expressed genes between experimental conditions. Generally, the workflow includes quality control of reads, mapping to a reference, counting transcript abundance, and statistical tests for differentially expressed genes. In spite of the numerous tools developed for each component of an RNA-seq analysis workflow, easy-to-use bacterially oriented workflow applications to combine multiple tools and automate the process are lacking. With many tools to choose from for each step, the task of identifying a specific tool, adapting the input/output options to the specific use-case, and integrating the tools into a coherent analysis pipeline is not a trivial endeavor, particularly for microbiologists with limited bioinformatics experience. To make bacterial RNA-seq data analysis more accessible, we developed a Simple Program for Automated reference-based bacterial RNA-seq Transcriptome Analysis (SPARTA). SPARTA is a reference-based bacterial RNA-seq analysis workflow application for single-end Illumina reads. SPARTA is turnkey software that simplifies the process of analyzing RNA-seq data sets, making bacterial RNA-seq analysis a routine process that can be undertaken on a personal computer or in the classroom. The easy-to-install, complete workflow processes whole transcriptome shotgun sequencing data files by trimming reads and removing adapters, mapping reads to a reference, counting gene features, calculating differential gene expression, and, importantly, checking for potential batch effects within the data set. SPARTA outputs quality analysis reports, gene feature counts and differential gene expression tables and scatterplots. SPARTA provides an easy-to-use bacterial RNA-seq transcriptional profiling workflow to identify differentially expressed genes between experimental conditions. This software will enable microbiologists with limited bioinformatics experience to analyze their data and integrate next generation sequencing (NGS) technologies into the classroom. The SPARTA software and tutorial are available at sparta.readthedocs.org.

Computational analysis of conserved RNA secondary structure in transcriptomes and genomes.

PubMed

Eddy, Sean R

2014-01-01

Transcriptomics experiments and computational predictions both enable systematic discovery of new functional RNAs. However, many putative noncoding transcripts arise instead from artifacts and biological noise, and current computational prediction methods have high false positive rates. I discuss prospects for improving computational methods for analyzing and identifying functional RNAs, with a focus on detecting signatures of conserved RNA secondary structure. An interesting new front is the application of chemical and enzymatic experiments that probe RNA structure on a transcriptome-wide scale. I review several proposed approaches for incorporating structure probing data into the computational prediction of RNA secondary structure. Using probabilistic inference formalisms, I show how all these approaches can be unified in a well-principled framework, which in turn allows RNA probing data to be easily integrated into a wide range of analyses that depend on RNA secondary structure inference. Such analyses include homology search and genome-wide detection of new structural RNAs.

Brain Radiation Information Data Exchange (BRIDE): integration of experimental data from low-dose ionising radiation research for pathway discovery.

PubMed

Karapiperis, Christos; Kempf, Stefan J; Quintens, Roel; Azimzadeh, Omid; Vidal, Victoria Linares; Pazzaglia, Simonetta; Bazyka, Dimitry; Mastroberardino, Pier G; Scouras, Zacharias G; Tapio, Soile; Benotmane, Mohammed Abderrafi; Ouzounis, Christos A

2016-05-11

The underlying molecular processes representing stress responses to low-dose ionising radiation (LDIR) in mammals are just beginning to be understood. In particular, LDIR effects on the brain and their possible association with neurodegenerative disease are currently being explored using omics technologies. We describe a light-weight approach for the storage, analysis and distribution of relevant LDIR omics datasets. The data integration platform, called BRIDE, contains information from the literature as well as experimental information from transcriptomics and proteomics studies. It deploys a hybrid, distributed solution using both local storage and cloud technology. BRIDE can act as a knowledge broker for LDIR researchers, to facilitate molecular research on the systems biology of LDIR response in mammals. Its flexible design can capture a range of experimental information for genomics, epigenomics, transcriptomics, and proteomics. The data collection is available at: .

Interpreter of maladies: redescription mining applied to biomedical data analysis.

PubMed

Waltman, Peter; Pearlman, Alex; Mishra, Bud

2006-04-01

Comprehensive, systematic and integrated data-centric statistical approaches to disease modeling can provide powerful frameworks for understanding disease etiology. Here, one such computational framework based on redescription mining in both its incarnations, static and dynamic, is discussed. The static framework provides bioinformatic tools applicable to multifaceted datasets, containing genetic, transcriptomic, proteomic, and clinical data for diseased patients and normal subjects. The dynamic redescription framework provides systems biology tools to model complex sets of regulatory, metabolic and signaling pathways in the initiation and progression of a disease. As an example, the case of chronic fatigue syndrome (CFS) is considered, which has so far remained intractable and unpredictable in its etiology and nosology. The redescription mining approaches can be applied to the Centers for Disease Control and Prevention's Wichita (KS, USA) dataset, integrating transcriptomic, epidemiological and clinical data, and can also be used to study how pathways in the hypothalamic-pituitary-adrenal axis affect CFS patients.

Longitudinal analysis of the group A Streptococcus transcriptome in experimental pharyngitis in cynomolgus macaques.

PubMed

Virtaneva, Kimmo; Porcella, Stephen F; Graham, Morag R; Ireland, Robin M; Johnson, Claire A; Ricklefs, Stacy M; Babar, Imran; Parkins, Larye D; Romero, Romina A; Corn, G Judson; Gardner, Don J; Bailey, John R; Parnell, Michael J; Musser, James M

2005-06-21

Identification of the genetic events that contribute to host-pathogen interactions is important for understanding the natural history of infectious diseases and developing therapeutics. Transcriptome studies conducted on pathogens have been central to this goal in recent years. However, most of these investigations have focused on specific end points or disease phases, rather than analysis of the entire time course of infection. To gain a more complete understanding of how bacterial gene expression changes over time in a primate host, the transcriptome of group A Streptococcus (GAS) was analyzed during an 86-day infection protocol in 20 cynomolgus macaques with experimental pharyngitis. The study used 260 custom Affymetrix (Santa Clara, CA) chips, and data were confirmed by TaqMan analysis. Colonization, acute, and asymptomatic phases of disease were identified. Successful colonization and severe inflammation were significantly correlated with an early onset of superantigen gene expression. The differential expression of two-component regulators covR and spy0680 (M1_spy0874) was significantly associated with GAS colony-forming units, inflammation, and phases of disease. Prophage virulence gene expression and prophage induction occurred predominantly during high pathogen cell densities and acute inflammation. We discovered that temporal changes in the GAS transcriptome were integrally linked to the phase of clinical disease and host-defense response. Knowledge of the gene expression patterns characterizing each phase of pathogen-host interaction provides avenues for targeted investigation of proven and putative virulence factors and genes of unknown function and will assist vaccine research.

Integrated phospholipidomics and transcriptomics analysis of Saccharomyces cerevisiae with enhanced tolerance to a mixture of acetic acid, furfural, and phenol

USDA-ARS?s Scientific Manuscript database

A mixture of acetic acid, furfural and phenol (AFP), three representative lignocellulose derived inhibitors, significantly inhibited the growth and bioethanol production of Saccharomyces cerevisiae. In order to uncover mechanisms behind the enhanced tolerance of an inhibitor-tolerant S.cerevisiae s...

Comparison between Proteome and Transcriptome Response in Potato (Solanum tuberosum L.) Leaves Following Potato Virus Y (PVY) Infection.

PubMed

Stare, Tjaša; Stare, Katja; Weckwerth, Wolfram; Wienkoop, Stefanie; Gruden, Kristina

2017-07-06

Plant diseases caused by viral infection are affecting all major crops. Being an obligate intracellular organisms, chemical control of these pathogens is so far not applied in the field except to control the insect vectors of the viruses. Understanding of molecular responses of plant immunity is therefore economically important, guiding the enforcement of crop resistance. To disentangle complex regulatory mechanisms of the plant immune responses, understanding system as a whole is a must. However, integrating data from different molecular analysis (transcriptomics, proteomics, metabolomics, smallRNA regulation etc.) is not straightforward. We evaluated the response of potato ( Solanum tuberosum L.) following the infection with potato virus Y (PVY). The response has been analyzed on two molecular levels, with microarray transcriptome analysis and mass spectroscopy-based proteomics. Within this report, we performed detailed analysis of the results on both levels and compared two different approaches for analysis of proteomic data (spectral count versus MaxQuant). To link the data on different molecular levels, each protein was mapped to the corresponding potato transcript according to StNIB paralogue grouping. Only 33% of the proteins mapped to microarray probes in a one-to-one relation and additionally many showed discordance in detected levels of proteins with corresponding transcripts. We discussed functional importance of true biological differences between both levels and showed that the reason for the discordance between transcript and protein abundance lies partly in complexity and structure of biological regulation of proteome and transcriptome and partly in technical issues contributing to it.

Comparison between Proteome and Transcriptome Response in Potato (Solanum tuberosum L.) Leaves Following Potato Virus Y (PVY) Infection

PubMed Central

Stare, Tjaša; Stare, Katja; Weckwerth, Wolfram; Wienkoop, Stefanie

2017-01-01

Plant diseases caused by viral infection are affecting all major crops. Being an obligate intracellular organisms, chemical control of these pathogens is so far not applied in the field except to control the insect vectors of the viruses. Understanding of molecular responses of plant immunity is therefore economically important, guiding the enforcement of crop resistance. To disentangle complex regulatory mechanisms of the plant immune responses, understanding system as a whole is a must. However, integrating data from different molecular analysis (transcriptomics, proteomics, metabolomics, smallRNA regulation etc.) is not straightforward. We evaluated the response of potato (Solanum tuberosum L.) following the infection with potato virus Y (PVY). The response has been analyzed on two molecular levels, with microarray transcriptome analysis and mass spectroscopy-based proteomics. Within this report, we performed detailed analysis of the results on both levels and compared two different approaches for analysis of proteomic data (spectral count versus MaxQuant). To link the data on different molecular levels, each protein was mapped to the corresponding potato transcript according to StNIB paralogue grouping. Only 33% of the proteins mapped to microarray probes in a one-to-one relation and additionally many showed discordance in detected levels of proteins with corresponding transcripts. We discussed functional importance of true biological differences between both levels and showed that the reason for the discordance between transcript and protein abundance lies partly in complexity and structure of biological regulation of proteome and transcriptome and partly in technical issues contributing to it. PMID:28684682

MiSTIC, an integrated platform for the analysis of heterogeneity in large tumour transcriptome datasets

PubMed Central

Sargeant, Tobias; Laperrière, David; Ismail, Houssam; Boucher, Geneviève; Rozendaal, Marieke; Lavallée, Vincent-Philippe; Ashton-Beaucage, Dariel; Wilhelm, Brian; Hébert, Josée; Hilton, Douglas J.

2017-01-01

Abstract Genome-wide transcriptome profiling has enabled non-supervised classification of tumours, revealing different sub-groups characterized by specific gene expression features. However, the biological significance of these subtypes remains for the most part unclear. We describe herein an interactive platform, Minimum Spanning Trees Inferred Clustering (MiSTIC), that integrates the direct visualization and comparison of the gene correlation structure between datasets, the analysis of the molecular causes underlying co-variations in gene expression in cancer samples, and the clinical annotation of tumour sets defined by the combined expression of selected biomarkers. We have used MiSTIC to highlight the roles of specific transcription factors in breast cancer subtype specification, to compare the aspects of tumour heterogeneity targeted by different prognostic signatures, and to highlight biomarker interactions in AML. A version of MiSTIC preloaded with datasets described herein can be accessed through a public web server (http://mistic.iric.ca); in addition, the MiSTIC software package can be obtained (github.com/iric-soft/MiSTIC) for local use with personalized datasets. PMID:28472340

Histological Stratification of Thick and Thin Plaque Psoriasis Explores Molecular Phenotypes with Clinical Implications

PubMed Central

Kim, Dong Joo; Brodmerkel, Carrie; Correa da Rosa, Joel; Krueger, James G.; Suárez-Fariñas, Mayte

2015-01-01

Psoriasis, which presents as red, scaly patches on the body, is a common, autoimmune skin disease that affects 2 to 3 percent of the world population. To leverage recent molecular findings into the personalized treatment of psoriasis, we need a strategy that integrates clinical stratification with molecular phenotyping. In this study, we sought to stratify psoriasis patients by histological measurements of epidermal thickness, and to compare their molecular characterizations by gene expression, serum cytokines, and response to biologics. We obtained histological measures of epidermal thickness in a cohort of 609 psoriasis patients, and identified a mixture of two subpopulations—thick and thin plaque psoriasis—from which they were derived. This stratification was verified in a subcohort of 65 patients from a previously published study with significant differences in inflammatory cell infiltrates in the psoriatic skin. Thick and thin plaque psoriasis shared 84.8% of the meta-analysis-derived psoriasis transcriptome, but a stronger dysregulation of the meta-analysis-derived psoriasis transcriptome was seen in thick plaque psoriasis on microarray. RT-PCR revealed that gene expression in thick and thin plaque psoriasis was different not only within psoriatic lesional skin but also in peripheral non-lesional skin. Additionally, differences in circulating cytokines and their changes in response to biologic treatments were found between the two subgroups. All together, we were able to integrate histological stratification with molecular phenotyping as a way of exploring clinical phenotypes with different expression levels of the psoriasis transcriptome and circulating cytokines. PMID:26176783

Integrated analyses using RNA-Seq data reveal viral genomes, single nucleotide variations, the phylogenetic relationship, and recombination for Apple stem grooving virus.

PubMed

Jo, Yeonhwa; Choi, Hoseong; Kim, Sang-Min; Kim, Sun-Lim; Lee, Bong Choon; Cho, Won Kyong

2016-08-09

Next-generation sequencing (NGS) provides many possibilities for plant virology research. In this study, we performed integrated analyses using plant transcriptome data for plant virus identification using Apple stem grooving virus (ASGV) as an exemplar virus. We used 15 publicly available transcriptome libraries from three different studies, two mRNA-Seq studies and a small RNA-Seq study. We de novo assembled nearly complete genomes of ASGV isolates Fuji and Cuiguan from apple and pear transcriptomes, respectively, and identified single nucleotide variations (SNVs) of ASGV within the transcriptomes. We demonstrated the application of NGS raw data to confirm viral infections in the plant transcriptomes. In addition, we compared the usability of two de novo assemblers, Trinity and Velvet, for virus identification and genome assembly. A phylogenetic tree revealed that ASGV and Citrus tatter leaf virus (CTLV) are the same virus, which was divided into two clades. Recombination analyses identified six recombination events from 21 viral genomes. Taken together, our in silico analyses using NGS data provide a successful application of plant transcriptomes to reveal extensive information associated with viral genome assembly, SNVs, phylogenetic relationships, and genetic recombination.

Transcriptomic meta-analysis identifies gene expression characteristics in various samples of HIV-infected patients with nonprogressive disease.

PubMed

Zhang, Le-Le; Zhang, Zi-Ning; Wu, Xian; Jiang, Yong-Jun; Fu, Ya-Jing; Shang, Hong

2017-09-12

A small proportion of HIV-infected patients remain clinically and/or immunologically stable for years, including elite controllers (ECs) who have undetectable viremia (<50 copies/ml) and long-term nonprogressors (LTNPs) who maintain normal CD4 + T cell counts for prolonged periods (>10 years). However, the mechanism of nonprogression needs to be further resolved. In this study, a transcriptome meta-analysis was performed on nonprogressor and progressor microarray data to identify differential transcriptome pathways and potential biomarkers. Using the INMEX (integrative meta-analysis of expression data) program, we performed the meta-analysis to identify consistently differentially expressed genes (DEGs) in nonprogressors and further performed functional interpretation (gene ontology analysis and pathway analysis) of the DEGs identified in the meta-analysis. Five microarray datasets (81 cases and 98 controls in total), including whole blood, CD4 + and CD8 + T cells, were collected for meta-analysis. We determined that nonprogressors have reduced expression of important interferon-stimulated genes (ISGs), CD38, lymphocyte activation gene 3 (LAG-3) in whole blood, CD4 + and CD8 + T cells. Gene ontology (GO) analysis showed a significant enrichment in DEGs that function in the type I interferon signaling pathway. Upregulated pathways, including the PI3K-Akt signaling pathway in whole blood, cytokine-cytokine receptor interaction in CD4 + T cells and the MAPK signaling pathway in CD8 + T cells, were identified in nonprogressors compared with progressors. In each metabolic functional category, the number of downregulated DEGs was more than the upregulated DEGs, and almost all genes were downregulated DEGs in the oxidative phosphorylation (OXPHOS) and tricarboxylic acid (TCA) cycle in the three types of samples. Our transcriptomic meta-analysis provides a comprehensive evaluation of the gene expression profiles in major blood types of nonprogressors, providing new insights in the understanding of HIV pathogenesis and developing strategies to delay HIV disease progression.

TRAPR: R Package for Statistical Analysis and Visualization of RNA-Seq Data.

PubMed

Lim, Jae Hyun; Lee, Soo Youn; Kim, Ju Han

2017-03-01

High-throughput transcriptome sequencing, also known as RNA sequencing (RNA-Seq), is a standard technology for measuring gene expression with unprecedented accuracy. Numerous bioconductor packages have been developed for the statistical analysis of RNA-Seq data. However, these tools focus on specific aspects of the data analysis pipeline, and are difficult to appropriately integrate with one another due to their disparate data structures and processing methods. They also lack visualization methods to confirm the integrity of the data and the process. In this paper, we propose an R-based RNA-Seq analysis pipeline called TRAPR, an integrated tool that facilitates the statistical analysis and visualization of RNA-Seq expression data. TRAPR provides various functions for data management, the filtering of low-quality data, normalization, transformation, statistical analysis, data visualization, and result visualization that allow researchers to build customized analysis pipelines.

Integrating Genomic Analysis with the Genetic Basis of Gene Expression: Preliminary Evidence of the Identification of Causal Genes for Cardiovascular and Metabolic Traits Related to Nutrition in Mexicans123

PubMed Central

Bastarrachea, Raúl A.; Gallegos-Cabriales, Esther C.; Nava-González, Edna J.; Haack, Karin; Voruganti, V. Saroja; Charlesworth, Jac; Laviada-Molina, Hugo A.; Veloz-Garza, Rosa A.; Cardenas-Villarreal, Velia Margarita; Valdovinos-Chavez, Salvador B.; Gomez-Aguilar, Patricia; Meléndez, Guillermo; López-Alvarenga, Juan Carlos; Göring, Harald H. H.; Cole, Shelley A.; Blangero, John; Comuzzie, Anthony G.; Kent, Jack W.

2012-01-01

Whole-transcriptome expression profiling provides novel phenotypes for analysis of complex traits. Gene expression measurements reflect quantitative variation in transcript-specific messenger RNA levels and represent phenotypes lying close to the action of genes. Understanding the genetic basis of gene expression will provide insight into the processes that connect genotype to clinically significant traits representing a central tenet of system biology. Synchronous in vivo expression profiles of lymphocytes, muscle, and subcutaneous fat were obtained from healthy Mexican men. Most genes were expressed at detectable levels in multiple tissues, and RNA levels were correlated between tissue types. A subset of transcripts with high reliability of expression across tissues (estimated by intraclass correlation coefficients) was enriched for cis-regulated genes, suggesting that proximal sequence variants may influence expression similarly in different cellular environments. This integrative global gene expression profiling approach is proving extremely useful for identifying genes and pathways that contribute to complex clinical traits. Clearly, the coincidence of clinical trait quantitative trait loci and expression quantitative trait loci can help in the prioritization of positional candidate genes. Such data will be crucial for the formal integration of positional and transcriptomic information characterized as genetical genomics. PMID:22797999

Influence of socioeconomic status on the whole blood transcriptome in African Americans.

PubMed

Gaye, Amadou; Gibbons, Gary H; Barry, Charles; Quarells, Rakale; Davis, Sharon K

2017-01-01

The correlation between low socioeconomic status (SES) and poor health outcome or higher risk of disease has been consistently reported by many epidemiological studies across various race/ancestry groups. However, the biological mechanisms linking low SES to disease and/or disease risk factors are not well understood and remain relatively under-studied. The analysis of the blood transcriptome is a promising window for elucidating how social and environmental factors influence the molecular networks governing health and disease. To further define the mechanistic pathways between social determinants and health, this study examined the impact of SES on the blood transcriptome in a sample of African-Americans. An integrative approach leveraging three complementary methods (Weighted Gene Co-expression Network Analysis, Random Forest and Differential Expression) was adopted to identify the most predictive and robust transcriptome pathways associated with SES. We analyzed the expression of 15079 genes (RNA-seq) from whole blood across 36 samples. The results revealed a cluster of 141 co-expressed genes over-expressed in the low SES group. Three pro-inflammatory pathways (IL-8 Signaling, NF-κB Signaling and Dendritic Cell Maturation) are activated in this module and over-expressed in low SES. Random Forest analysis revealed 55 of the 141 genes that, collectively, predict SES with an area under the curve of 0.85. One third of the 141 genes are significantly over-expressed in the low SES group. Lower SES has consistently been linked to many social and environmental conditions acting as stressors and known to be correlated with vulnerability to chronic illnesses (e.g. asthma, diabetes) associated with a chronic inflammatory state. Our unbiased analysis of the blood transcriptome in African-Americans revealed evidence of a robust molecular signature of increased inflammation associated with low SES. The results provide a plausible link between the social factors and chronic inflammation.

Network Analysis of Rodent Transcriptomes in Spaceflight

NASA Technical Reports Server (NTRS)

Ramachandran, Maya; Fogle, Homer; Costes, Sylvain

2017-01-01

Network analysis methods leverage prior knowledge of cellular systems and the statistical and conceptual relationships between analyte measurements to determine gene connectivity. Correlation and conditional metrics are used to infer a network topology and provide a systems-level context for cellular responses. Integration across multiple experimental conditions and omics domains can reveal the regulatory mechanisms that underlie gene expression. GeneLab has assembled rich multi-omic (transcriptomics, proteomics, epigenomics, and epitranscriptomics) datasets for multiple murine tissues from the Rodent Research 1 (RR-1) experiment. RR-1 assesses the impact of 37 days of spaceflight on gene expression across a variety of tissue types, such as adrenal glands, quadriceps, gastrocnemius, tibalius anterior, extensor digitorum longus, soleus, eye, and kidney. Network analysis is particularly useful for RR-1 -omics datasets because it reinforces subtle relationships that may be overlooked in isolated analyses and subdues confounding factors. Our objective is to use network analysis to determine potential target nodes for therapeutic intervention and identify similarities with existing disease models. Multiple network algorithms are used for a higher confidence consensus.

Trinity | Informatics Technology for Cancer Research (ITCR)

Cancer.gov

Trinity Cancer Transcriptome Analysis Toolkit (CTAT) including de novo transcriptome assembly with downstream support for expression analysis and focused analyses on cancer transcriptomes, incorporating mutation and fusion transcript discovery, and single cell analysis.

Resources and Recommendations for Using Transcriptomics to Address Grand Challenges in Comparative Biology.

PubMed

Mykles, Donald L; Burnett, Karen G; Durica, David S; Joyce, Blake L; McCarthy, Fiona M; Schmidt, Carl J; Stillman, Jonathon H

2016-12-01

High-throughput RNA sequencing (RNA-seq) technology has become an important tool for studying physiological responses of organisms to changes in their environment. De novo assembly of RNA-seq data has allowed researchers to create a comprehensive catalog of genes expressed in a tissue and to quantify their expression without a complete genome sequence. The contributions from the "Tapping the Power of Crustacean Transcriptomics to Address Grand Challenges in Comparative Biology" symposium in this issue show the successes and limitations of using RNA-seq in the study of crustaceans. In conjunction with the symposium, the Animal Genome to Phenome Research Coordination Network collated comments from participants at the meeting regarding the challenges encountered when using transcriptomics in their research. Input came from novices and experts ranging from graduate students to principal investigators. Many were unaware of the bioinformatics analysis resources currently available on the CyVerse platform. Our analysis of community responses led to three recommendations for advancing the field: (1) integration of genomic and RNA-seq sequence assemblies for crustacean gene annotation and comparative expression; (2) development of methodologies for the functional analysis of genes; and (3) information and training exchange among laboratories for transmission of best practices. The field lacks the methods for manipulating tissue-specific gene expression. The decapod crustacean research community should consider the cherry shrimp, Neocaridina denticulata, as a decapod model for the application of transgenic tools for functional genomics. This would require a multi-investigator effort. © The Author 2016. Published by Oxford University Press on behalf of the Society for Integrative and Comparative Biology. All rights reserved. For permissions please email: journals.permissions@oup.com.

Combined venomics, antivenomics and venom gland transcriptome analysis of the monocoled cobra (Naja kaouthia) from China.

PubMed

Xu, Ning; Zhao, Hong-Yan; Yin, Yin; Shen, Shan-Shan; Shan, Lin-Lin; Chen, Chuan-Xi; Zhang, Yan-Xia; Gao, Jian-Fang; Ji, Xiang

2017-04-21

We conducted an omics-analysis of the venom of Naja kaouthia from China. Proteomics analysis revealed six protein families [three-finger toxins (3-FTx), phospholipase A 2 (PLA 2 ), nerve growth factor, snake venom metalloproteinase (SVMP), cysteine-rich secretory protein and ohanin], and venom-gland transcriptomics analysis revealed 28 protein families from 79 unigenes. 3-FTx (56.5% in proteome/82.0% in transcriptome) and PLA 2 (26.9%/13.6%) were identified as the most abundant families in venom proteome and venom-gland transcriptome. Furthermore, N. kaouthia venom expressed strong lethality (i.p. LD 50 : 0.79μg/g) and myotoxicity (CK: 5939U/l) in mice, and showed notable activity in PLA 2 but weak activity in SVMP, l-amino acid oxidase or 5' nucleotidase. Antivenomic assessment revealed that several venom components (nearly 17.5% of total venom) from N. kaouthia could not be thoroughly immunocaptured by commercial Naja atra antivenom. ELISA analysis revealed that there was no difference in the cross-reaction between N. kaouthia and N. atra venoms against the N. atra antivenom. The use of commercial N. atra antivenom in treatment of snakebites caused by N. kaouthia is reasonable, but design of novel antivenom with the attention on enhancing the immune response of non-immunocaptured components should be encouraged. The venomics, antivenomics and venom-gland transcriptome of the monocoled cobra (Naja kaouthia) from China have been elucidated. Quantitative and qualitative differences are evident when venom proteomic and venom-gland transcriptomic profiles are compared. Two protein families (3-FTx and PLA 2 ) are found to be the predominated components in N. kaouthia venom, and considered as the major players in functional role of venom. Other protein families with relatively low abundance appear to be minor in the functional significance. Antivenomics and ELISA evaluation reveal that the N. kaouthia venom can be effectively immunorecognized by commercial N. atra antivenom, but still a small number of venom components could not be thoroughly immunocaptured. The findings indicate that exploring the precise composition of snake venom should be executed by an integrated omics-approach, and elucidating the venom composition is helpful in understanding composition-function relationships and will facilitate the clinical application of antivenoms. Copyright © 2017 Elsevier B.V. All rights reserved.

Combined transcriptome and metabolome analyses of metformin effects reveal novel links between metabolic networks in steroidogenic systems.

PubMed

Udhane, Sameer S; Legeza, Balazs; Marti, Nesa; Hertig, Damian; Diserens, Gaëlle; Nuoffer, Jean-Marc; Vermathen, Peter; Flück, Christa E

2017-08-17

Metformin is an antidiabetic drug, which inhibits mitochondrial respiratory-chain-complex I and thereby seems to affect the cellular metabolism in many ways. It is also used for the treatment of the polycystic ovary syndrome (PCOS), the most common endocrine disorder in women. In addition, metformin possesses antineoplastic properties. Although metformin promotes insulin-sensitivity and ameliorates reproductive abnormalities in PCOS, its exact mechanisms of action remain elusive. Therefore, we studied the transcriptome and the metabolome of metformin in human adrenal H295R cells. Microarray analysis revealed changes in 693 genes after metformin treatment. Using high resolution magic angle spinning nuclear magnetic resonance spectroscopy (HR-MAS-NMR), we determined 38 intracellular metabolites. With bioinformatic tools we created an integrated pathway analysis to understand different intracellular processes targeted by metformin. Combined metabolomics and transcriptomics data analysis showed that metformin affects a broad range of cellular processes centered on the mitochondrium. Data confirmed several known effects of metformin on glucose and androgen metabolism, which had been identified in clinical and basic studies previously. But more importantly, novel links between the energy metabolism, sex steroid biosynthesis, the cell cycle and the immune system were identified. These omics studies shed light on a complex interplay between metabolic pathways in steroidogenic systems.

Systems perspectives on erythromycin biosynthesis by comparative genomic and transcriptomic analyses of S. erythraea E3 and NRRL23338 strains

PubMed Central

2013-01-01

Background S. erythraea is a Gram-positive filamentous bacterium used for the industrial-scale production of erythromycin A which is of high clinical importance. In this work, we sequenced the whole genome of a high-producing strain (E3) obtained by random mutagenesis and screening from the wild-type strain NRRL23338, and examined time-series expression profiles of both E3 and NRRL23338. Based on the genomic data and transcriptpmic data of these two strains, we carried out comparative analysis of high-producing strain and wild-type strain at both the genomic level and the transcriptomic level. Results We observed a large number of genetic variants including 60 insertions, 46 deletions and 584 single nucleotide variations (SNV) in E3 in comparison with NRRL23338, and the analysis of time series transcriptomic data indicated that the genes involved in erythromycin biosynthesis and feeder pathways were significantly up-regulated during the 60 hours time-course. According to our data, BldD, a previously identified ery cluster regulator, did not show any positive correlations with the expression of ery cluster, suggesting the existence of alternative regulation mechanisms of erythromycin synthesis in S. erythraea. Several potential regulators were then proposed by integration analysis of genomic and transcriptomic data. Conclusion This is a demonstration of the functional comparative genomics between an industrial S. erythraea strain and the wild-type strain. These findings help to understand the global regulation mechanisms of erythromycin biosynthesis in S. erythraea, providing useful clues for genetic and metabolic engineering in the future. PMID:23902230

Transcriptome and metabolome analysis of plant sulfate starvation and resupply provides novel information on transcriptional regulation of metabolism associated with sulfur, nitrogen and phosphorus nutritional responses in Arabidopsis

PubMed Central

Bielecka, Monika; Watanabe, Mutsumi; Morcuende, Rosa; Scheible, Wolf-Rüdiger; Hawkesford, Malcolm J.; Hesse, Holger; Hoefgen, Rainer

2015-01-01

Sulfur is an essential macronutrient for plant growth and development. Reaching a thorough understanding of the molecular basis for changes in plant metabolism depending on the sulfur-nutritional status at the systems level will advance our basic knowledge and help target future crop improvement. Although the transcriptional responses induced by sulfate starvation have been studied in the past, knowledge of the regulation of sulfur metabolism is still fragmentary. This work focuses on the discovery of candidates for regulatory genes such as transcription factors (TFs) using ‘omics technologies. For this purpose a short term sulfate-starvation/re-supply approach was used. ATH1 microarray studies and metabolite determinations yielded 21 TFs which responded more than 2-fold at the transcriptional level to sulfate starvation. Categorization by response behaviors under sulfate-starvation/re-supply and other nutrient starvations such as nitrate and phosphate allowed determination of whether the TF genes are specific for or common between distinct mineral nutrient depletions. Extending this co-behavior analysis to the whole transcriptome data set enabled prediction of putative downstream genes. Additionally, combinations of transcriptome and metabolome data allowed identification of relationships between TFs and downstream responses, namely, expression changes in biosynthetic genes and subsequent metabolic responses. Effect chains on glucosinolate and polyamine biosynthesis are discussed in detail. The knowledge gained from this study provides a blueprint for an integrated analysis of transcriptomics and metabolomics and application for the identification of uncharacterized genes. PMID:25674096

Methods, Tools and Current Perspectives in Proteogenomics *

PubMed Central

Ruggles, Kelly V.; Krug, Karsten; Wang, Xiaojing; Clauser, Karl R.; Wang, Jing; Payne, Samuel H.; Fenyö, David; Zhang, Bing; Mani, D. R.

2017-01-01

With combined technological advancements in high-throughput next-generation sequencing and deep mass spectrometry-based proteomics, proteogenomics, i.e. the integrative analysis of proteomic and genomic data, has emerged as a new research field. Early efforts in the field were focused on improving protein identification using sample-specific genomic and transcriptomic sequencing data. More recently, integrative analysis of quantitative measurements from genomic and proteomic studies have identified novel insights into gene expression regulation, cell signaling, and disease. Many methods and tools have been developed or adapted to enable an array of integrative proteogenomic approaches and in this article, we systematically classify published methods and tools into four major categories, (1) Sequence-centric proteogenomics; (2) Analysis of proteogenomic relationships; (3) Integrative modeling of proteogenomic data; and (4) Data sharing and visualization. We provide a comprehensive review of methods and available tools in each category and highlight their typical applications. PMID:28456751

Population and allelic variation of A-to-I RNA editing in human transcriptomes.

PubMed

Park, Eddie; Guo, Jiguang; Shen, Shihao; Demirdjian, Levon; Wu, Ying Nian; Lin, Lan; Xing, Yi

2017-07-28

A-to-I RNA editing is an important step in RNA processing in which specific adenosines in some RNA molecules are post-transcriptionally modified to inosines. RNA editing has emerged as a widespread mechanism for generating transcriptome diversity. However, there remain significant knowledge gaps about the variation and function of RNA editing. In order to determine the influence of genetic variation on A-to-I RNA editing, we integrate genomic and transcriptomic data from 445 human lymphoblastoid cell lines by combining an RNA editing QTL (edQTL) analysis with an allele-specific RNA editing (ASED) analysis. We identify 1054 RNA editing events associated with cis genetic polymorphisms. Additionally, we find that a subset of these polymorphisms is linked to genome-wide association study signals of complex traits or diseases. Finally, compared to random cis polymorphisms, polymorphisms associated with RNA editing variation are located closer spatially to their respective editing sites and have a more pronounced impact on RNA secondary structure. Our study reveals widespread cis variation in RNA editing among genetically distinct individuals and sheds light on possible phenotypic consequences of such variation on complex traits and diseases.

Comparative Transcriptomic Characterization of the Early Development in Pacific White Shrimp Litopenaeus vannamei

PubMed Central

Wei, Jiankai; Zhang, Xiaojun; Yu, Yang; Huang, Hao; Li, Fuhua; Xiang, Jianhai

2014-01-01

Penaeid shrimp has a distinctive metamorphosis stage during early development. Although morphological and biochemical studies about this ontogeny have been developed for decades, researches on gene expression level are still scarce. In this study, we have investigated the transcriptomes of five continuous developmental stages in Pacific white shrimp (Litopenaeus vannamei) with high throughput Illumina sequencing technology. The reads were assembled and clustered into 66,815 unigenes, of which 32,398 have putative homologues in nr database, 14,981 have been classified into diverse functional categories by Gene Ontology (GO) annotation and 26,257 have been associated with 255 pathways by KEGG pathway mapping. Meanwhile, the differentially expressed genes (DEGs) between adjacent developmental stages were identified and gene expression patterns were clustered. By GO term enrichment analysis, KEGG pathway enrichment analysis and functional gene profiling, the physiological changes during shrimp metamorphosis could be better understood, especially histogenesis, diet transition, muscle development and exoskeleton reconstruction. In conclusion, this is the first study that characterized the integrated transcriptomic profiles during early development of penaeid shrimp, and these findings will serve as significant references for shrimp developmental biology and aquaculture research. PMID:25197823

A comparative in silico linear B-cell epitope prediction and characterization for South American and African Trypanosoma vivax strains.

PubMed

Guedes, Rafael Lucas Muniz; Rodrigues, Carla Monadeli Filgueira; Coatnoan, Nicolas; Cosson, Alain; Cadioli, Fabiano Antonio; Garcia, Herakles Antonio; Gerber, Alexandra Lehmkuhl; Machado, Rosangela Zacarias; Minoprio, Paola Marcella Camargo; Teixeira, Marta Maria Geraldes; de Vasconcelos, Ana Tereza Ribeiro

2018-02-27

Trypanosoma vivax is a parasite widespread across Africa and South America. Immunological methods using recombinant antigens have been developed aiming at specific and sensitive detection of infections caused by T. vivax. Here, we sequenced for the first time the transcriptome of a virulent T. vivax strain (Lins), isolated from an outbreak of severe disease in South America (Brazil) and performed a computational integrated analysis of genome, transcriptome and in silico predictions to identify and characterize putative linear B-cell epitopes from African and South American T. vivax. A total of 2278, 3936 and 4062 linear B-cell epitopes were respectively characterized for the transcriptomes of T. vivax LIEM-176 (Venezuela), T. vivax IL1392 (Nigeria) and T. vivax Lins (Brazil) and 4684 for the genome of T. vivax Y486 (Nigeria). The results presented are a valuable theoretical source that may pave the way for highly sensitive and specific diagnostic tools. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

[Applications of meta-analysis in multi-omics].

PubMed

Han, Mingfei; Zhu, Yunping

2014-07-01

As a statistical method integrating multi-features and multi-data, meta-analysis was introduced to the field of life science in the 1990s. With the rapid advances in high-throughput technologies, life omics, the core of which are genomics, transcriptomics and proteomics, is becoming the new hot spot of life science. Although the fast output of massive data has promoted the development of omics study, it results in excessive data that are difficult to integrate systematically. In this case, meta-analysis is frequently applied to analyze different types of data and is improved continuously. Here, we first summarize the representative meta-analysis methods systematically, and then study the current applications of meta-analysis in various omics fields, finally we discuss the still-existing problems and the future development of meta-analysis.

Primary Respiratory Chain Disease Causes Tissue-Specific Dysregulation of the Global Transcriptome and Nutrient-Sensing Signaling Network

PubMed Central

Zhang, Zhe; Tsukikawa, Mai; Peng, Min; Polyak, Erzsebet; Nakamaru-Ogiso, Eiko; Ostrovsky, Julian; McCormack, Shana; Place, Emily; Clarke, Colleen; Reiner, Gail; McCormick, Elizabeth; Rappaport, Eric; Haas, Richard; Baur, Joseph A.; Falk, Marni J.

2013-01-01

Primary mitochondrial respiratory chain (RC) diseases are heterogeneous in etiology and manifestations but collectively impair cellular energy metabolism. Mechanism(s) by which RC dysfunction causes global cellular sequelae are poorly understood. To identify a common cellular response to RC disease, integrated gene, pathway, and systems biology analyses were performed in human primary RC disease skeletal muscle and fibroblast transcriptomes. Significant changes were evident in muscle across diverse RC complex and genetic etiologies that were consistent with prior reports in other primary RC disease models and involved dysregulation of genes involved in RNA processing, protein translation, transport, and degradation, and muscle structure. Global transcriptional and post-transcriptional dysregulation was also found to occur in a highly tissue-specific fashion. In particular, RC disease muscle had decreased transcription of cytosolic ribosomal proteins suggestive of reduced anabolic processes, increased transcription of mitochondrial ribosomal proteins, shorter 5′-UTRs that likely improve translational efficiency, and stabilization of 3′-UTRs containing AU-rich elements. RC disease fibroblasts showed a strikingly similar pattern of global transcriptome dysregulation in a reverse direction. In parallel with these transcriptional effects, RC disease dysregulated the integrated nutrient-sensing signaling network involving FOXO, PPAR, sirtuins, AMPK, and mTORC1, which collectively sense nutrient availability and regulate cellular growth. Altered activities of central nodes in the nutrient-sensing signaling network were validated by phosphokinase immunoblot analysis in RC inhibited cells. Remarkably, treating RC mutant fibroblasts with nicotinic acid to enhance sirtuin and PPAR activity also normalized mTORC1 and AMPK signaling, restored NADH/NAD+ redox balance, and improved cellular respiratory capacity. These data specifically highlight a common pathogenesis extending across different molecular and biochemical etiologies of individual RC disorders that involves global transcriptome modifications. We further identify the integrated nutrient-sensing signaling network as a common cellular response that mediates, and may be amenable to targeted therapies for, tissue-specific sequelae of primary mitochondrial RC disease. PMID:23894440

De novo sequencing and characterization of floral transcriptome in two species of buckwheat (Fagopyrum)

PubMed Central

2011-01-01

Background Transcriptome sequencing data has become an integral component of modern genetics, genomics and evolutionary biology. However, despite advances in the technologies of DNA sequencing, such data are lacking for many groups of living organisms, in particular, many plant taxa. We present here the results of transcriptome sequencing for two closely related plant species. These species, Fagopyrum esculentum and F. tataricum, belong to the order Caryophyllales - a large group of flowering plants with uncertain evolutionary relationships. F. esculentum (common buckwheat) is also an important food crop. Despite these practical and evolutionary considerations Fagopyrum species have not been the subject of large-scale sequencing projects. Results Normalized cDNA corresponding to genes expressed in flowers and inflorescences of F. esculentum and F. tataricum was sequenced using the 454 pyrosequencing technology. This resulted in 267 (for F. esculentum) and 229 (F. tataricum) thousands of reads with average length of 341-349 nucleotides. De novo assembly of the reads produced about 25 thousands of contigs for each species, with 7.5-8.2× coverage. Comparative analysis of two transcriptomes demonstrated their overall similarity but also revealed genes that are presumably differentially expressed. Among them are retrotransposon genes and genes involved in sugar biosynthesis and metabolism. Thirteen single-copy genes were used for phylogenetic analysis; the resulting trees are largely consistent with those inferred from multigenic plastid datasets. The sister relationships of the Caryophyllales and asterids now gained high support from nuclear gene sequences. Conclusions 454 transcriptome sequencing and de novo assembly was performed for two congeneric flowering plant species, F. esculentum and F. tataricum. As a result, a large set of cDNA sequences that represent orthologs of known plant genes as well as potential new genes was generated. PMID:21232141

Integrated transcriptome sequencing and dynamic analysis reveal carbon source partitioning between terpenoid and oil accumulation in developing Lindera glauca fruits.

PubMed

Niu, Jun; Chen, Yinlei; An, Jiyong; Hou, Xinyu; Cai, Jian; Wang, Jia; Zhang, Zhixiang; Lin, Shanzhi

2015-10-08

Lindera glauca fruits (LGF) with the abundance of terpenoid and oil has emerged as a novel specific material for industrial and medicinal application in China, but the complex regulatory mechanisms of carbon source partitioning into terpenoid biosynthetic pathway (TBP) and oil biosynthetic pathway (OBP) in developing LGF is still unknown. Here we perform the analysis of contents and compositions of terpenoid and oil from 7 stages of developing LGF to characterize a dramatic difference in temporal accumulative patterns. The resulting 3 crucial samples at 50, 125 and 150 days after flowering (DAF) were selected for comparative deep transcriptome analysis. By Illumina sequencing, the obtained approximately 81 million reads are assembled into 69,160 unigenes, among which 174, 71, 81 and 155 unigenes are implicated in glycolysis, pentose phosphate pathway (PPP), TBP and OBP, respectively. Integrated differential expression profiling and qRT-PCR, we specifically characterize the key enzymes and transcription factors (TFs) involved in regulating carbon allocation ratios for terpenoid or oil accumulation in developing LGF. These results contribute to our understanding of the regulatory mechanisms of carbon source partitioning between terpenoid and oil in developing LGF, and to the improvement of resource utilization and molecular breeding for L. glauca.

MiSTIC, an integrated platform for the analysis of heterogeneity in large tumour transcriptome datasets.

PubMed

Lemieux, Sebastien; Sargeant, Tobias; Laperrière, David; Ismail, Houssam; Boucher, Geneviève; Rozendaal, Marieke; Lavallée, Vincent-Philippe; Ashton-Beaucage, Dariel; Wilhelm, Brian; Hébert, Josée; Hilton, Douglas J; Mader, Sylvie; Sauvageau, Guy

2017-07-27

Genome-wide transcriptome profiling has enabled non-supervised classification of tumours, revealing different sub-groups characterized by specific gene expression features. However, the biological significance of these subtypes remains for the most part unclear. We describe herein an interactive platform, Minimum Spanning Trees Inferred Clustering (MiSTIC), that integrates the direct visualization and comparison of the gene correlation structure between datasets, the analysis of the molecular causes underlying co-variations in gene expression in cancer samples, and the clinical annotation of tumour sets defined by the combined expression of selected biomarkers. We have used MiSTIC to highlight the roles of specific transcription factors in breast cancer subtype specification, to compare the aspects of tumour heterogeneity targeted by different prognostic signatures, and to highlight biomarker interactions in AML. A version of MiSTIC preloaded with datasets described herein can be accessed through a public web server (http://mistic.iric.ca); in addition, the MiSTIC software package can be obtained (github.com/iric-soft/MiSTIC) for local use with personalized datasets. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

AMPKα Modulation in Cancer Progression: Multilayer Integrative Analysis of the Whole Transcriptome in Asian Gastric Cancer

PubMed Central

Cho, Jae Yong; Cheong, Jae-Ho; Kim, Hoguen; Li, Min; Downey, Thomas J.; Dyer, Matthew D.; Sun, Yongming; Sun, Jingtao; Beasley, Ellen M.; Chung, Hyun Cheol; Noh, Sung Hoon; Weinstein, John N.; Liu, Chang-Gong; Powis, Garth

2013-01-01

Gastric cancer is the most common cancer in Asia and most developing countries. Despite the use of multimodality therapeutics, it remains the second leading cause of cancer death in the world. To identify the molecular underpinnings of gastric cancer in the Asian population, we applied an RNA-sequencing approach to gastric tumor and noncancerous specimens, generating 680 million informative short reads to quantitatively characterize the entire transcriptome of gastric cancer (including mRNAs and microRNAs). A multi-layer analysis was then developed to identify multiple types of transcriptional aberrations associated with different stages of gastric cancer, including differentially expressed mRNAs, recurrent somatic mutations and key differentially expressed microRNAs. Through this approach, we identified the central metabolic regulator AMPK-α as a potential functional target in Asian gastric cancer. Further, we experimentally demonstrated the translational relevance of this gene as a potential therapeutic target for early-stage gastric cancer in Asian patients. Together, our findings not only provide a valuable information resource for identifying and elucidating the molecular mechanisms of Asian gastric cancer, but also represent a general integrative framework to develop more effective therapeutic targets. PMID:22434430

Characterization and analysis of a transcriptome from the boreal spider crab Hyas araneus.

PubMed

Harms, Lars; Frickenhaus, Stephan; Schiffer, Melanie; Mark, Felix C; Storch, Daniela; Pörtner, Hans-Otto; Held, Christoph; Lucassen, Magnus

2013-12-01

Research investigating the genetic basis of physiological responses has significantly broadened our understanding of the mechanisms underlying organismic response to environmental change. However, genomic data are currently available for few taxa only, thus excluding physiological model species from this approach. In this study we report the transcriptome of the model organism Hyas araneus from Spitsbergen (Arctic). We generated 20,479 transcripts, using the 454 GS FLX sequencing technology in combination with an Illumina HiSeq sequencing approach. Annotation by Blastx revealed 7159 blast hits in the NCBI non-redundant protein database. The comparison between the spider crab H. araneus transcriptome and EST libraries of the European lobster Homarus americanus and the porcelain crab Petrolisthes cinctipes yielded 3229/2581 sequences with a significant hit, respectively. The clustering by the Markov Clustering Algorithm (MCL) revealed a common core of 1710 clusters present in all three species and 5903 unique clusters for H. araneus. The combined sequencing approaches generated transcripts that will greatly expand the limited genomic data available for crustaceans. We introduce the MCL clustering for transcriptome comparisons as a simple approach to estimate similarities between transcriptomic libraries of different size and quality and to analyze homologies within the selected group of species. In particular, we identified a large variety of reverse transcriptase (RT) sequences not only in the H. araneus transcriptome and other decapod crustaceans, but also sea urchin, supporting the hypothesis of a heritable, anti-viral immunity and the proposed viral fragment integration by host-derived RTs in marine invertebrates. © 2013.

A combination of LongSAGE with Solexa sequencing is well suited to explore the depth and the complexity of transcriptome

PubMed Central

Hanriot, Lucie; Keime, Céline; Gay, Nadine; Faure, Claudine; Dossat, Carole; Wincker, Patrick; Scoté-Blachon, Céline; Peyron, Christelle; Gandrillon, Olivier

2008-01-01

Background "Open" transcriptome analysis methods allow to study gene expression without a priori knowledge of the transcript sequences. As of now, SAGE (Serial Analysis of Gene Expression), LongSAGE and MPSS (Massively Parallel Signature Sequencing) are the mostly used methods for "open" transcriptome analysis. Both LongSAGE and MPSS rely on the isolation of 21 pb tag sequences from each transcript. In contrast to LongSAGE, the high throughput sequencing method used in MPSS enables the rapid sequencing of very large libraries containing several millions of tags, allowing deep transcriptome analysis. However, a bias in the complexity of the transcriptome representation obtained by MPSS was recently uncovered. Results In order to make a deep analysis of mouse hypothalamus transcriptome avoiding the limitation introduced by MPSS, we combined LongSAGE with the Solexa sequencing technology and obtained a library of more than 11 millions of tags. We then compared it to a LongSAGE library of mouse hypothalamus sequenced with the Sanger method. Conclusion We found that Solexa sequencing technology combined with LongSAGE is perfectly suited for deep transcriptome analysis. In contrast to MPSS, it gives a complex representation of transcriptome as reliable as a LongSAGE library sequenced by the Sanger method. PMID:18796152

Linking gene regulation and the exo-metabolome: A comparative transcriptomics approach to identify genes that impact on the production of volatile aroma compounds in yeast

PubMed Central

Rossouw, Debra; Næs, Tormod; Bauer, Florian F

2008-01-01

Background 'Omics' tools provide novel opportunities for system-wide analysis of complex cellular functions. Secondary metabolism is an example of a complex network of biochemical pathways, which, although well mapped from a biochemical point of view, is not well understood with regards to its physiological roles and genetic and biochemical regulation. Many of the metabolites produced by this network such as higher alcohols and esters are significant aroma impact compounds in fermentation products, and different yeast strains are known to produce highly divergent aroma profiles. Here, we investigated whether we can predict the impact of specific genes of known or unknown function on this metabolic network by combining whole transcriptome and partial exo-metabolome analysis. Results For this purpose, the gene expression levels of five different industrial wine yeast strains that produce divergent aroma profiles were established at three different time points of alcoholic fermentation in synthetic wine must. A matrix of gene expression data was generated and integrated with the concentrations of volatile aroma compounds measured at the same time points. This relatively unbiased approach to the study of volatile aroma compounds enabled us to identify candidate genes for aroma profile modification. Five of these genes, namely YMR210W, BAT1, AAD10, AAD14 and ACS1 were selected for overexpression in commercial wine yeast, VIN13. Analysis of the data show a statistically significant correlation between the changes in the exo-metabome of the overexpressing strains and the changes that were predicted based on the unbiased alignment of transcriptomic and exo-metabolomic data. Conclusion The data suggest that a comparative transcriptomics and metabolomics approach can be used to identify the metabolic impacts of the expression of individual genes in complex systems, and the amenability of transcriptomic data to direct applications of biotechnological relevance. PMID:18990252

A bioinformatics transcriptome meta-analysis highlights the importance of trophoblast differentiation in the pathology of hydatidiform moles.

PubMed

Desterke, Christophe; Slim, Rima; Candelier, Jean-Jacques

2018-05-01

Hydatidiform mole (HM) is an aberrant human pregnancy with abnormal trophoblastic development, migration/invasion of the extravillous trophoblast in the decidua. These abnormalities are established in a hypoxic environment during the first trimester of gestation. Using text mining, we identified 72 unique genes that are linked to HM (HM-linked genes) that we studied by bioinformatic analysis in publicly available transcriptomes of primary chorionic villous cells (cytotrophoblast, syncytiotrophoblast, extravillous trophoblast, and arterial and venous endothelial) isolated from normal placentas or established trophoblastic cell lines cultured under different oxygen concentrations. We show that the majority of HM-linked genes (75%) are involved in normal trophoblastic differentiation, arranged in clusters, and some of them are implicated in chorionic villous invasion or regulated by oxygen concentrations. Our analysis integrates the various aspects of the pathophysiology of HM and highlights the importance of trophoblastic differentiation in this pathology. Copyright © 2018 Elsevier Ltd. All rights reserved.

Improving wood properties for wood utilization through multi-omics integration in lignin biosynthesis

DOE PAGES

Wang, Jack P.; Matthews, Megan L.; Williams, Cranos M.; ...

2018-04-20

A multi-omics quantitative integrative analysis of lignin biosynthesis can advance the strategic engineering of wood for timber, pulp, and biofuels. Lignin is polymerized from three monomers (monolignols) produced by a grid-like pathway. The pathway in wood formation of Populus trichocarpa has at least 21 genes, encoding enzymes that mediate 37 reactions on 24 metabolites, leading to lignin and affecting wood properties. We perturb these 21 pathway genes and integrate transcriptomic, proteomic, fluxomic and phenomic data from 221 lines selected from ~2000 transgenics (6-month-old). The integrative analysis estimates how changing expression of pathway gene or gene combination affects protein abundance, metabolic-flux,more » metabolite concentrations, and 25 wood traits, including lignin, tree-growth, density, strength, and saccharification. The analysis then predicts improvements in any of these 25 traits individually or in combinations, through engineering expression of specific monolignol genes. The analysis may lead to greater understanding of other pathways for improved growth and adaptation.« less

Improving wood properties for wood utilization through multi-omics integration in lignin biosynthesis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Jack P.; Matthews, Megan L.; Williams, Cranos M.

A multi-omics quantitative integrative analysis of lignin biosynthesis can advance the strategic engineering of wood for timber, pulp, and biofuels. Lignin is polymerized from three monomers (monolignols) produced by a grid-like pathway. The pathway in wood formation of Populus trichocarpa has at least 21 genes, encoding enzymes that mediate 37 reactions on 24 metabolites, leading to lignin and affecting wood properties. We perturb these 21 pathway genes and integrate transcriptomic, proteomic, fluxomic and phenomic data from 221 lines selected from ~2000 transgenics (6-month-old). The integrative analysis estimates how changing expression of pathway gene or gene combination affects protein abundance, metabolic-flux,more » metabolite concentrations, and 25 wood traits, including lignin, tree-growth, density, strength, and saccharification. The analysis then predicts improvements in any of these 25 traits individually or in combinations, through engineering expression of specific monolignol genes. The analysis may lead to greater understanding of other pathways for improved growth and adaptation.« less

Improving wood properties for wood utilization through multi-omics integration in lignin biosynthesis.

PubMed

Wang, Jack P; Matthews, Megan L; Williams, Cranos M; Shi, Rui; Yang, Chenmin; Tunlaya-Anukit, Sermsawat; Chen, Hsi-Chuan; Li, Quanzi; Liu, Jie; Lin, Chien-Yuan; Naik, Punith; Sun, Ying-Hsuan; Loziuk, Philip L; Yeh, Ting-Feng; Kim, Hoon; Gjersing, Erica; Shollenberger, Todd; Shuford, Christopher M; Song, Jina; Miller, Zachary; Huang, Yung-Yun; Edmunds, Charles W; Liu, Baoguang; Sun, Yi; Lin, Ying-Chung Jimmy; Li, Wei; Chen, Hao; Peszlen, Ilona; Ducoste, Joel J; Ralph, John; Chang, Hou-Min; Muddiman, David C; Davis, Mark F; Smith, Chris; Isik, Fikret; Sederoff, Ronald; Chiang, Vincent L

2018-04-20

A multi-omics quantitative integrative analysis of lignin biosynthesis can advance the strategic engineering of wood for timber, pulp, and biofuels. Lignin is polymerized from three monomers (monolignols) produced by a grid-like pathway. The pathway in wood formation of Populus trichocarpa has at least 21 genes, encoding enzymes that mediate 37 reactions on 24 metabolites, leading to lignin and affecting wood properties. We perturb these 21 pathway genes and integrate transcriptomic, proteomic, fluxomic and phenomic data from 221 lines selected from ~2000 transgenics (6-month-old). The integrative analysis estimates how changing expression of pathway gene or gene combination affects protein abundance, metabolic-flux, metabolite concentrations, and 25 wood traits, including lignin, tree-growth, density, strength, and saccharification. The analysis then predicts improvements in any of these 25 traits individually or in combinations, through engineering expression of specific monolignol genes. The analysis may lead to greater understanding of other pathways for improved growth and adaptation.

Integrative biology approach identifies cytokine targeting strategies for psoriasis.

PubMed

Perera, Gayathri K; Ainali, Chrysanthi; Semenova, Ekaterina; Hundhausen, Christian; Barinaga, Guillermo; Kassen, Deepika; Williams, Andrew E; Mirza, Muddassar M; Balazs, Mercedesz; Wang, Xiaoting; Rodriguez, Robert Sanchez; Alendar, Andrej; Barker, Jonathan; Tsoka, Sophia; Ouyang, Wenjun; Nestle, Frank O

2014-02-12

Cytokines are critical checkpoints of inflammation. The treatment of human autoimmune disease has been revolutionized by targeting inflammatory cytokines as key drivers of disease pathogenesis. Despite this, there exist numerous pitfalls when translating preclinical data into the clinic. We developed an integrative biology approach combining human disease transcriptome data sets with clinically relevant in vivo models in an attempt to bridge this translational gap. We chose interleukin-22 (IL-22) as a model cytokine because of its potentially important proinflammatory role in epithelial tissues. Injection of IL-22 into normal human skin grafts produced marked inflammatory skin changes resembling human psoriasis. Injection of anti-IL-22 monoclonal antibody in a human xenotransplant model of psoriasis, developed specifically to test potential therapeutic candidates, efficiently blocked skin inflammation. Bioinformatic analysis integrating both the IL-22 and anti-IL-22 cytokine transcriptomes and mapping them onto a psoriasis disease gene coexpression network identified key cytokine-dependent hub genes. Using knockout mice and small-molecule blockade, we show that one of these hub genes, the so far unexplored serine/threonine kinase PIM1, is a critical checkpoint for human skin inflammation and potential future therapeutic target in psoriasis. Using in silico integration of human data sets and biological models, we were able to identify a new target in the treatment of psoriasis.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kolker, Eugene

Our project focused primarily on analysis of different types of data produced by global high-throughput technologies, data integration of gene annotation, and gene and protein expression information, as well as on getting a better functional annotation of Shewanella genes. Specifically, four of our numerous major activities and achievements include the development of: statistical models for identification and expression proteomics, superior to currently available approaches (including our own earlier ones); approaches to improve gene annotations on the whole-organism scale; standards for annotation, transcriptomics and proteomics approaches; and generalized approaches for data integration of gene annotation, gene and protein expression information.

TranscriptomeBrowser 3.0: introducing a new compendium of molecular interactions and a new visualization tool for the study of gene regulatory networks.

PubMed

Lepoivre, Cyrille; Bergon, Aurélie; Lopez, Fabrice; Perumal, Narayanan B; Nguyen, Catherine; Imbert, Jean; Puthier, Denis

2012-01-31

Deciphering gene regulatory networks by in silico approaches is a crucial step in the study of the molecular perturbations that occur in diseases. The development of regulatory maps is a tedious process requiring the comprehensive integration of various evidences scattered over biological databases. Thus, the research community would greatly benefit from having a unified database storing known and predicted molecular interactions. Furthermore, given the intrinsic complexity of the data, the development of new tools offering integrated and meaningful visualizations of molecular interactions is necessary to help users drawing new hypotheses without being overwhelmed by the density of the subsequent graph. We extend the previously developed TranscriptomeBrowser database with a set of tables containing 1,594,978 human and mouse molecular interactions. The database includes: (i) predicted regulatory interactions (computed by scanning vertebrate alignments with a set of 1,213 position weight matrices), (ii) potential regulatory interactions inferred from systematic analysis of ChIP-seq experiments, (iii) regulatory interactions curated from the literature, (iv) predicted post-transcriptional regulation by micro-RNA, (v) protein kinase-substrate interactions and (vi) physical protein-protein interactions. In order to easily retrieve and efficiently analyze these interactions, we developed In-teractomeBrowser, a graph-based knowledge browser that comes as a plug-in for Transcriptome-Browser. The first objective of InteractomeBrowser is to provide a user-friendly tool to get new insight into any gene list by providing a context-specific display of putative regulatory and physical interactions. To achieve this, InteractomeBrowser relies on a "cell compartments-based layout" that makes use of a subset of the Gene Ontology to map gene products onto relevant cell compartments. This layout is particularly powerful for visual integration of heterogeneous biological information and is a productive avenue in generating new hypotheses. The second objective of InteractomeBrowser is to fill the gap between interaction databases and dynamic modeling. It is thus compatible with the network analysis software Cytoscape and with the Gene Interaction Network simulation software (GINsim). We provide examples underlying the benefits of this visualization tool for large gene set analysis related to thymocyte differentiation. The InteractomeBrowser plugin is a powerful tool to get quick access to a knowledge database that includes both predicted and validated molecular interactions. InteractomeBrowser is available through the TranscriptomeBrowser framework and can be found at: http://tagc.univ-mrs.fr/tbrowser/. Our database is updated on a regular basis.

Integrative Genome-Scale Analysis Identifies Epigenetic Mechanisms of Transcriptional Deregulation in Unfavorable Neuroblastomas.

PubMed

Henrich, Kai-Oliver; Bender, Sebastian; Saadati, Maral; Dreidax, Daniel; Gartlgruber, Moritz; Shao, Chunxuan; Herrmann, Carl; Wiesenfarth, Manuel; Parzonka, Martha; Wehrmann, Lea; Fischer, Matthias; Duffy, David J; Bell, Emma; Torkov, Alica; Schmezer, Peter; Plass, Christoph; Höfer, Thomas; Benner, Axel; Pfister, Stefan M; Westermann, Frank

2016-09-15

The broad clinical spectrum of neuroblastoma ranges from spontaneous regression to rapid progression despite intensive multimodal therapy. This diversity is not fully explained by known genetic aberrations, suggesting the possibility of epigenetic involvement in pathogenesis. In pursuit of this hypothesis, we took an integrative approach to analyze the methylomes, transcriptomes, and copy number variations in 105 cases of neuroblastoma, complemented by primary tumor- and cell line-derived global histone modification analyses and epigenetic drug treatment in vitro We found that DNA methylation patterns identify divergent patient subgroups with respect to survival and clinicobiologic variables, including amplified MYCN Transcriptome integration and histone modification-based definition of enhancer elements revealed intragenic enhancer methylation as a mechanism for high-risk-associated transcriptional deregulation. Furthermore, in high-risk neuroblastomas, we obtained evidence for cooperation between PRC2 activity and DNA methylation in blocking tumor-suppressive differentiation programs. Notably, these programs could be re-activated by combination treatments, which targeted both PRC2 and DNA methylation. Overall, our results illuminate how epigenetic deregulation contributes to neuroblastoma pathogenesis, with novel implications for its diagnosis and therapy. Cancer Res; 76(18); 5523-37. ©2016 AACR. ©2016 American Association for Cancer Research.

An integrated analysis of genes and functional pathways for aggression in human and rodent models.

PubMed

Zhang-James, Yanli; Fernàndez-Castillo, Noèlia; Hess, Jonathan L; Malki, Karim; Glatt, Stephen J; Cormand, Bru; Faraone, Stephen V

2018-06-01

Human genome-wide association studies (GWAS), transcriptome analyses of animal models, and candidate gene studies have advanced our understanding of the genetic architecture of aggressive behaviors. However, each of these methods presents unique limitations. To generate a more confident and comprehensive view of the complex genetics underlying aggression, we undertook an integrated, cross-species approach. We focused on human and rodent models to derive eight gene lists from three main categories of genetic evidence: two sets of genes identified in GWAS studies, four sets implicated by transcriptome-wide studies of rodent models, and two sets of genes with causal evidence from online Mendelian inheritance in man (OMIM) and knockout (KO) mice reports. These gene sets were evaluated for overlap and pathway enrichment to extract their similarities and differences. We identified enriched common pathways such as the G-protein coupled receptor (GPCR) signaling pathway, axon guidance, reelin signaling in neurons, and ERK/MAPK signaling. Also, individual genes were ranked based on their cumulative weights to quantify their importance as risk factors for aggressive behavior, which resulted in 40 top-ranked and highly interconnected genes. The results of our cross-species and integrated approach provide insights into the genetic etiology of aggression.

A Bioinformatics Approach for Integrated Transcriptomic and Proteomic Comparative Analyses of Model and Non-sequenced Anopheline Vectors of Human Malaria Parasites*

PubMed Central

Mohien, Ceereena Ubaida; Colquhoun, David R.; Mathias, Derrick K.; Gibbons, John G.; Armistead, Jennifer S.; Rodriguez, Maria C.; Rodriguez, Mario Henry; Edwards, Nathan J.; Hartler, Jürgen; Thallinger, Gerhard G.; Graham, David R.; Martinez-Barnetche, Jesus; Rokas, Antonis; Dinglasan, Rhoel R.

2013-01-01

Malaria morbidity and mortality caused by both Plasmodium falciparum and Plasmodium vivax extend well beyond the African continent, and although P. vivax causes between 80 and 300 million severe cases each year, vivax transmission remains poorly understood. Plasmodium parasites are transmitted by Anopheles mosquitoes, and the critical site of interaction between parasite and host is at the mosquito's luminal midgut brush border. Although the genome of the “model” African P. falciparum vector, Anopheles gambiae, has been sequenced, evolutionary divergence limits its utility as a reference across anophelines, especially non-sequenced P. vivax vectors such as Anopheles albimanus. Clearly, technologies and platforms that bridge this substantial scientific gap are required in order to provide public health scientists with key transcriptomic and proteomic information that could spur the development of novel interventions to combat this disease. To our knowledge, no approaches have been published that address this issue. To bolster our understanding of P. vivax–An. albimanus midgut interactions, we developed an integrated bioinformatic-hybrid RNA-Seq-LC-MS/MS approach involving An. albimanus transcriptome (15,764 contigs) and luminal midgut subproteome (9,445 proteins) assembly, which, when used with our custom Diptera protein database (685,078 sequences), facilitated a comparative proteomic analysis of the midgut brush borders of two important malaria vectors, An. gambiae and An. albimanus. PMID:23082028

A bioinformatics approach for integrated transcriptomic and proteomic comparative analyses of model and non-sequenced anopheline vectors of human malaria parasites.

PubMed

Ubaida Mohien, Ceereena; Colquhoun, David R; Mathias, Derrick K; Gibbons, John G; Armistead, Jennifer S; Rodriguez, Maria C; Rodriguez, Mario Henry; Edwards, Nathan J; Hartler, Jürgen; Thallinger, Gerhard G; Graham, David R; Martinez-Barnetche, Jesus; Rokas, Antonis; Dinglasan, Rhoel R

2013-01-01

Malaria morbidity and mortality caused by both Plasmodium falciparum and Plasmodium vivax extend well beyond the African continent, and although P. vivax causes between 80 and 300 million severe cases each year, vivax transmission remains poorly understood. Plasmodium parasites are transmitted by Anopheles mosquitoes, and the critical site of interaction between parasite and host is at the mosquito's luminal midgut brush border. Although the genome of the "model" African P. falciparum vector, Anopheles gambiae, has been sequenced, evolutionary divergence limits its utility as a reference across anophelines, especially non-sequenced P. vivax vectors such as Anopheles albimanus. Clearly, technologies and platforms that bridge this substantial scientific gap are required in order to provide public health scientists with key transcriptomic and proteomic information that could spur the development of novel interventions to combat this disease. To our knowledge, no approaches have been published that address this issue. To bolster our understanding of P. vivax-An. albimanus midgut interactions, we developed an integrated bioinformatic-hybrid RNA-Seq-LC-MS/MS approach involving An. albimanus transcriptome (15,764 contigs) and luminal midgut subproteome (9,445 proteins) assembly, which, when used with our custom Diptera protein database (685,078 sequences), facilitated a comparative proteomic analysis of the midgut brush borders of two important malaria vectors, An. gambiae and An. albimanus.

A Transcriptomic Analysis of Cave, Surface, and Hybrid Isopod Crustaceans of the Species Asellus aquaticus

PubMed Central

Stahl, Bethany A.; Gross, Joshua B.; Speiser, Daniel I.; Oakley, Todd H.; Patel, Nipam H.; Gould, Douglas B.; Protas, Meredith E.

2015-01-01

Cave animals, compared to surface-dwelling relatives, tend to have reduced eyes and pigment, longer appendages, and enhanced mechanosensory structures. Pressing questions include how certain cave-related traits are gained and lost, and if they originate through the same or different genetic programs in independent lineages. An excellent system for exploring these questions is the isopod, Asellus aquaticus. This species includes multiple cave and surface populations that have numerous morphological differences between them. A key feature is that hybrids between cave and surface individuals are viable, which enables genetic crosses and linkage analyses. Here, we advance this system by analyzing single animal transcriptomes of Asellus aquaticus. We use high throughput sequencing of non-normalized cDNA derived from the head of a surface-dwelling male, the head of a cave-dwelling male, the head of a hybrid male (produced by crossing a surface individual with a cave individual), and a pooled sample of surface embryos and hatchlings. Assembling reads from surface and cave head RNA pools yielded an integrated transcriptome comprised of 23,984 contigs. Using this integrated assembly as a reference transcriptome, we aligned reads from surface-, cave- and hybrid- head tissue and pooled surface embryos and hatchlings. Our approach identified 742 SNPs and placed four new candidate genes to an existing linkage map for A. aquaticus. In addition, we examined SNPs for allele-specific expression differences in the hybrid individual. All of these resources will facilitate identification of genes and associated changes responsible for cave adaptation in A. aquaticus and, in concert with analyses of other species, will inform our understanding of the evolutionary processes accompanying adaptation to the subterranean environment. PMID:26462237

iMETHYL: an integrative database of human DNA methylation, gene expression, and genomic variation.

PubMed

Komaki, Shohei; Shiwa, Yuh; Furukawa, Ryohei; Hachiya, Tsuyoshi; Ohmomo, Hideki; Otomo, Ryo; Satoh, Mamoru; Hitomi, Jiro; Sobue, Kenji; Sasaki, Makoto; Shimizu, Atsushi

2018-01-01

We launched an integrative multi-omics database, iMETHYL (http://imethyl.iwate-megabank.org). iMETHYL provides whole-DNA methylation (~24 million autosomal CpG sites), whole-genome (~9 million single-nucleotide variants), and whole-transcriptome (>14 000 genes) data for CD4 + T-lymphocytes, monocytes, and neutrophils collected from approximately 100 subjects. These data were obtained from whole-genome bisulfite sequencing, whole-genome sequencing, and whole-transcriptome sequencing, making iMETHYL a comprehensive database.

Gene coexpression network analysis of fruit transcriptomes uncovers a possible mechanistically distinct class of sugar/acid ratio-associated genes in sweet orange.

PubMed

Qiao, Liang; Cao, Minghao; Zheng, Jian; Zhao, Yihong; Zheng, Zhi-Liang

2017-10-30

The ratio of sugars to organic acids, two of the major metabolites in fleshy fruits, has been considered the most important contributor to fruit sweetness. Although accumulation of sugars and acids have been extensively studied, whether plants evolve a mechanism to maintain, sense or respond to the fruit sugar/acid ratio remains a mystery. In a prior study, we used an integrated systems biology tool to identify a group of 39 acid-associated genes from the fruit transcriptomes in four sweet orange varieties (Citrus sinensis L. Osbeck) with varying fruit acidity, Succari (acidless), Bingtang (low acid), and Newhall and Xinhui (normal acid). We reanalyzed the prior sweet orange fruit transcriptome data, leading to the identification of 72 genes highly correlated with the fruit sugar/acid ratio. The majority of these sugar/acid ratio-related genes are predicted to be involved in regulatory functions such as transport, signaling and transcription or encode enzymes involved in metabolism. Surprisingly, only three of these sugar/acid ratio-correlated genes are weakly correlated with sugar level and none of them overlaps with the acid-associated genes. Weighted Gene Coexpression Network Analysis (WGCNA) has revealed that these genes belong to four modules, Blue, Grey, Brown and Turquoise, with the former two modules being unique to the sugar/acid ratio control. Our results indicate that orange fruits contain a possible mechanistically distinct class of genes that may potentially be involved in maintaining fruit sugar/acid ratios and/or responding to the cellular sugar/acid ratio status. Therefore, our analysis of orange transcriptomes provides an intriguing insight into the potentially novel genetic or molecular mechanisms controlling the sugar/acid ratio in fruits.

Transcriptome Analysis of Dendrobium officinale and its Application to the Identification of Genes Associated with Polysaccharide Synthesis

PubMed Central

Zhang, Jianxia; He, Chunmei; Wu, Kunlin; Teixeira da Silva, Jaime A.; Zeng, Songjun; Zhang, Xinhua; Yu, Zhenming; Xia, Haoqiang; Duan, Jun

2016-01-01

Dendrobium officinale is one of the most important Chinese medicinal herbs. Polysaccharides are one of the main active ingredients of D. officinale. To identify the genes that maybe related to polysaccharides synthesis, two cDNA libraries were prepared from juvenile and adult D. officinale, and were named Dendrobium-1 and Dendrobium-2, respectively. Illumina sequencing for Dendrobium-1 generated 102 million high quality reads that were assembled into 93,881 unigenes with an average sequence length of 790 base pairs. The sequencing for Dendrobium-2 generated 86 million reads that were assembled into 114,098 unigenes with an average sequence length of 695 base pairs. Two transcriptome databases were integrated and assembled into a total of 145,791 unigenes. Among them, 17,281 unigenes were assigned to 126 KEGG pathways while 135 unigenes were involved in fructose and mannose metabolism. Gene Ontology analysis revealed that the majority of genes were associated with metabolic and cellular processes. Furthermore, 430 glycosyltransferase and 89 cellulose synthase genes were identified. Comparative analysis of both transcriptome databases revealed a total of 32,794 differential expression genes (DEGs), including 22,051 up-regulated and 10,743 down-regulated genes in Dendrobium-2 compared to Dendrobium-1. Furthermore, a total of 1142 and 7918 unigenes showed unique expression in Dendrobium-1 and Dendrobium-2, respectively. These DEGs were mainly correlated with metabolic pathways and the biosynthesis of secondary metabolites. In addition, 170 DEGs belonged to glycosyltransferase genes, 37 DEGs were related to cellulose synthase genes and 627 DEGs encoded transcription factors. This study substantially expands the transcriptome information for D. officinale and provides valuable clues for identifying candidate genes involved in polysaccharide biosynthesis and elucidating the mechanism of polysaccharide biosynthesis. PMID:26904032

Octopus-toolkit: a workflow to automate mining of public epigenomic and transcriptomic next-generation sequencing data

PubMed Central

Kim, Taemook; Seo, Hogyu David; Hennighausen, Lothar; Lee, Daeyoup

2018-01-01

Abstract Octopus-toolkit is a stand-alone application for retrieving and processing large sets of next-generation sequencing (NGS) data with a single step. Octopus-toolkit is an automated set-up-and-analysis pipeline utilizing the Aspera, SRA Toolkit, FastQC, Trimmomatic, HISAT2, STAR, Samtools, and HOMER applications. All the applications are installed on the user's computer when the program starts. Upon the installation, it can automatically retrieve original files of various epigenomic and transcriptomic data sets, including ChIP-seq, ATAC-seq, DNase-seq, MeDIP-seq, MNase-seq and RNA-seq, from the gene expression omnibus data repository. The downloaded files can then be sequentially processed to generate BAM and BigWig files, which are used for advanced analyses and visualization. Currently, it can process NGS data from popular model genomes such as, human (Homo sapiens), mouse (Mus musculus), dog (Canis lupus familiaris), plant (Arabidopsis thaliana), zebrafish (Danio rerio), fruit fly (Drosophila melanogaster), worm (Caenorhabditis elegans), and budding yeast (Saccharomyces cerevisiae) genomes. With the processed files from Octopus-toolkit, the meta-analysis of various data sets, motif searches for DNA-binding proteins, and the identification of differentially expressed genes and/or protein-binding sites can be easily conducted with few commands by users. Overall, Octopus-toolkit facilitates the systematic and integrative analysis of available epigenomic and transcriptomic NGS big data. PMID:29420797

Alternative splicing and trans-splicing events revealed by analysis of the Bombyx mori transcriptome

PubMed Central

Shao, Wei; Zhao, Qiong-Yi; Wang, Xiu-Ye; Xu, Xin-Yan; Tang, Qing; Li, Muwang; Li, Xuan; Xu, Yong-Zhen

2012-01-01

Alternative splicing and trans-splicing events have not been systematically studied in the silkworm Bombyx mori. Here, the silkworm transcriptome was analyzed by RNA-seq. We identified 320 novel genes, modified 1140 gene models, and found thousands of alternative splicing and 58 trans-splicing events. Studies of three SR proteins show that both their alternative splicing patterns and mRNA products are conserved from insect to human, and one isoform of Srsf6 with a retained intron is expressed sex-specifically in silkworm gonads. Trans-splicing of mod(mdg4) in silkworm was experimentally confirmed. We identified integrations from a common 5′-gene with 46 newly identified alternative 3′-exons that are located on both DNA strands over a 500-kb region. Other trans-splicing events in B. mori were predicted by bioinformatic analysis, in which 12 events were confirmed by RT-PCR, six events were further validated by chimeric SNPs, and two events were confirmed by allele-specific RT-PCR in F1 hybrids from distinct silkworm lines of JS and L10, indicating that trans-splicing is more widespread in insects than previously thought. Analysis of the B. mori transcriptome by RNA-seq provides valuable information of regulatory alternative splicing events. The conservation of splicing events across species and newly identified trans-splicing events suggest that B. mori is a good model for future studies. PMID:22627775

Growth in spaceflight hardware results in alterations to the transcriptome and proteome

NASA Astrophysics Data System (ADS)

Basu, Proma; Kruse, Colin P. S.; Luesse, Darron R.; Wyatt, Sarah E.

2017-11-01

The Biological Research in Canisters (BRIC) hardware has been used to house many biology experiments on both the Space Transport System (STS, commonly known as the space shuttle) and the International Space Station (ISS). However, microscopic examination of Arabidopsis seedlings by Johnson et al. (2015) indicated the hardware itself may affect cell morphology. The experiment herein was designed to assess the effects of the BRIC-Petri Dish Fixation Units (BRIC-PDFU) hardware on the transcriptome and proteome of Arabidopsis seedlings. To our knowledge, this is the first transcriptomic and proteomic comparison of Arabidopsis seedlings grown with and without hardware. Arabidopsis thaliana wild-type Columbia (Col-0) seeds were sterilized and bulk plated on forty-four 60 mm Petri plates, of which 22 were integrated into the BRIC-PDFU hardware and 22 were maintained in closed containers at Ohio University. Seedlings were grown for approximately 3 days, fixed with RNAlater® and stored at -80 °C prior to RNA and protein extraction, with proteins separated into membrane and soluble fractions prior to analysis. The RNAseq analysis identified 1651 differentially expressed genes; MS/MS analysis identified 598 soluble and 589 membrane proteins differentially abundant both at p < .05. Fold enrichment analysis of gene ontology terms related to differentially expressed transcripts and proteins highlighted a variety of stress responses. Some of these genes and proteins have been previously identified in spaceflight experiments, indicating that these genes and proteins may be perturbed by both conditions.

Towards the integration, annotation and association of historical microarray experiments with RNA-seq.

PubMed

Chavan, Shweta S; Bauer, Michael A; Peterson, Erich A; Heuck, Christoph J; Johann, Donald J

2013-01-01

Transcriptome analysis by microarrays has produced important advances in biomedicine. For instance in multiple myeloma (MM), microarray approaches led to the development of an effective disease subtyping via cluster assignment, and a 70 gene risk score. Both enabled an improved molecular understanding of MM, and have provided prognostic information for the purposes of clinical management. Many researchers are now transitioning to Next Generation Sequencing (NGS) approaches and RNA-seq in particular, due to its discovery-based nature, improved sensitivity, and dynamic range. Additionally, RNA-seq allows for the analysis of gene isoforms, splice variants, and novel gene fusions. Given the voluminous amounts of historical microarray data, there is now a need to associate and integrate microarray and RNA-seq data via advanced bioinformatic approaches. Custom software was developed following a model-view-controller (MVC) approach to integrate Affymetrix probe set-IDs, and gene annotation information from a variety of sources. The tool/approach employs an assortment of strategies to integrate, cross reference, and associate microarray and RNA-seq datasets. Output from a variety of transcriptome reconstruction and quantitation tools (e.g., Cufflinks) can be directly integrated, and/or associated with Affymetrix probe set data, as well as necessary gene identifiers and/or symbols from a diversity of sources. Strategies are employed to maximize the annotation and cross referencing process. Custom gene sets (e.g., MM 70 risk score (GEP-70)) can be specified, and the tool can be directly assimilated into an RNA-seq pipeline. A novel bioinformatic approach to aid in the facilitation of both annotation and association of historic microarray data, in conjunction with richer RNA-seq data, is now assisting with the study of MM cancer biology.

Comparative Transcriptomic Analysis of the Response of Dunaliella acidophila (Chlorophyta) to Short-Term Cadmium and Chronic Natural Metal-Rich Water Exposures.

PubMed

Puente-Sánchez, Fernando; Olsson, Sanna; Aguilera, Angeles

2016-10-01

Heavy metals are toxic compounds known to cause multiple and severe cellular damage. However, acidophilic extremophiles are able to cope with very high concentrations of heavy metals. This study investigated the stress response under natural environmental heavy metal concentrations in an acidophilic Dunaliella acidophila. We employed Illumina sequencing for a de novo transcriptome assembly and to identify changes in response to high cadmium concentrations and natural metal-rich water. The photosynthetic performance was also estimated by pulse amplitude-modulated (PAM) fluorescence. Transcriptomic analysis highlights a number of processes mainly related to a high constitutive expression of genes involved in oxidative stress and response to reactive oxygen species (ROS), even in the absence of heavy metals. Photosynthetic activity seems to be unaltered under short-term exposition to Cd and chronic exposure to natural metal-rich water, probably due to an increase in the synthesis of structural photosynthetic components preserving their functional integrity. An overrepresentation of Gene Ontology (GO) terms related to metabolic activities, transcription, and proteosomal catabolic process was observed when D. acidophila grew under chronic exposure to natural metal-rich water. GO terms involved in carbohydrate metabolic process, reticulum endoplasmic and Golgi bodies, were also specifically overrepresented in natural metal-rich water library suggesting an endoplasmic reticulum stress response.

Transcriptome analysis of Haloquadratum walsbyi: vanity is but the surface.

PubMed

Bolhuis, Henk; Martín-Cuadrado, Ana Belén; Rosselli, Riccardo; Pašić, Lejla; Rodriguez-Valera, Francisco

2017-07-03

Haloquadratum walsbyi dominates saturated thalassic lakes worldwide where they can constitute up to 80-90% of the total prokaryotic community. Despite the abundance of the enigmatic square-flattened cells, only 7 isolates are currently known with 2 genomes fully sequenced and annotated due to difficulties to grow them under laboratory conditions. We have performed a transcriptomic analysis of one of these isolates, the Spanish strain HBSQ001 in order to investigate gene transcription under light and dark conditions. Despite a potential advantage for light as additional source of energy, no significant differences were found between light and dark expressed genes. Constitutive high gene expression was observed in genes encoding surface glycoproteins, light mediated proton pumping by bacteriorhodopsin, several nutrient uptake systems, buoyancy and storage of excess carbon. Two low expressed regions of the genome were characterized by a lower codon adaptation index, low GC content and high incidence of hypothetical genes. Under the extant cultivation conditions, the square hyperhalophile devoted most of its transcriptome towards processes maintaining cell integrity and exploiting solar energy. Surface glycoproteins are essential for maintaining the large surface to volume ratio that facilitates light and organic nutrient harvesting whereas constitutive expression of bacteriorhodopsin warrants an immediate source of energy when light becomes available.

Transcriptome analysis on the exoskeleton formation in early developmetal stages and reconstruction scenario in growth-moulting in Litopenaeus vannamei.

PubMed

Gao, Yi; Wei, Jiankai; Yuan, Jianbo; Zhang, Xiaojun; Li, Fuhua; Xiang, Jianhai

2017-04-24

Exoskeleton construction is an important issue in shrimp. To better understand the molecular mechanism of exoskeleton formation, development and reconstruction, the transcriptome of the entire developmental process in Litopenaeus vannamei, including nine early developmental stages and eight adult-moulting stages, was sequenced and analysed using Illumina RNA-seq technology. A total of 117,539 unigenes were obtained, with 41.2% unigenes predicting the full-length coding sequence. Gene Ontology, Clusters of Orthologous Group (COG), the Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis and functional annotation of all unigenes gave a better understanding of the exoskeleton developmental process in L. vannamei. As a result, more than six hundred unigenes related to exoskeleton development were identified both in the early developmental stages and adult-moulting. A cascade of sequential expression events of exoskeleton-related genes were summarized, including exoskeleton formation, regulation, synthesis, degradation, mineral absorption/reabsorption, calcification and hardening. This new insight on major transcriptional events provide a deep understanding for exoskeleton formation and reconstruction in L. vannamei. In conclusion, this is the first study that characterized the integrated transcriptomic profiles cover the entire exoskeleton development from zygote to adult-moulting in a crustacean, and these findings will serve as significant references for exoskeleton developmental biology and aquaculture research.

Evolution of Daily Gene Co-expression Patterns from Algae to Plants

PubMed Central

de los Reyes, Pedro; Romero-Campero, Francisco J.; Ruiz, M. Teresa; Romero, José M.; Valverde, Federico

2017-01-01

Daily rhythms play a key role in transcriptome regulation in plants and microalgae orchestrating responses that, among other processes, anticipate light transitions that are essential for their metabolism and development. The recent accumulation of genome-wide transcriptomic data generated under alternating light:dark periods from plants and microalgae has made possible integrative and comparative analysis that could contribute to shed light on the evolution of daily rhythms in the green lineage. In this work, RNA-seq and microarray data generated over 24 h periods in different light regimes from the eudicot Arabidopsis thaliana and the microalgae Chlamydomonas reinhardtii and Ostreococcus tauri have been integrated and analyzed using gene co-expression networks. This analysis revealed a reduction in the size of the daily rhythmic transcriptome from around 90% in Ostreococcus, being heavily influenced by light transitions, to around 40% in Arabidopsis, where a certain independence from light transitions can be observed. A novel Multiple Bidirectional Best Hit (MBBH) algorithm was applied to associate single genes with a family of potential orthologues from evolutionary distant species. Gene duplication, amplification and divergence of rhythmic expression profiles seems to have played a central role in the evolution of gene families in the green lineage such as Pseudo Response Regulators (PRRs), CONSTANS-Likes (COLs), and DNA-binding with One Finger (DOFs). Gene clustering and functional enrichment have been used to identify groups of genes with similar rhythmic gene expression patterns. The comparison of gene clusters between species based on potential orthologous relationships has unveiled a low to moderate level of conservation of daily rhythmic expression patterns. However, a strikingly high conservation was found for the gene clusters exhibiting their highest and/or lowest expression value during the light transitions. PMID:28751903

Listeriomics: an Interactive Web Platform for Systems Biology of Listeria

PubMed Central

Koutero, Mikael; Tchitchek, Nicolas; Cerutti, Franck; Lechat, Pierre; Maillet, Nicolas; Hoede, Claire; Chiapello, Hélène; Gaspin, Christine

2017-01-01

ABSTRACT As for many model organisms, the amount of Listeria omics data produced has recently increased exponentially. There are now >80 published complete Listeria genomes, around 350 different transcriptomic data sets, and 25 proteomic data sets available. The analysis of these data sets through a systems biology approach and the generation of tools for biologists to browse these various data are a challenge for bioinformaticians. We have developed a web-based platform, named Listeriomics, that integrates different tools for omics data analyses, i.e., (i) an interactive genome viewer to display gene expression arrays, tiling arrays, and sequencing data sets along with proteomics and genomics data sets; (ii) an expression and protein atlas that connects every gene, small RNA, antisense RNA, or protein with the most relevant omics data; (iii) a specific tool for exploring protein conservation through the Listeria phylogenomic tree; and (iv) a coexpression network tool for the discovery of potential new regulations. Our platform integrates all the complete Listeria species genomes, transcriptomes, and proteomes published to date. This website allows navigation among all these data sets with enriched metadata in a user-friendly format and can be used as a central database for systems biology analysis. IMPORTANCE In the last decades, Listeria has become a key model organism for the study of host-pathogen interactions, noncoding RNA regulation, and bacterial adaptation to stress. To study these mechanisms, several genomics, transcriptomics, and proteomics data sets have been produced. We have developed Listeriomics, an interactive web platform to browse and correlate these heterogeneous sources of information. Our website will allow listeriologists and microbiologists to decipher key regulation mechanism by using a systems biology approach. PMID:28317029

Improving transcriptome construction in non-model organisms: integrating manual and automated gene definition in Emiliania huxleyi.

PubMed

Feldmesser, Ester; Rosenwasser, Shilo; Vardi, Assaf; Ben-Dor, Shifra

2014-02-22

The advent of Next Generation Sequencing technologies and corresponding bioinformatics tools allows the definition of transcriptomes in non-model organisms. Non-model organisms are of great ecological and biotechnological significance, and consequently the understanding of their unique metabolic pathways is essential. Several methods that integrate de novo assembly with genome-based assembly have been proposed. Yet, there are many open challenges in defining genes, particularly where genomes are not available or incomplete. Despite the large numbers of transcriptome assemblies that have been performed, quality control of the transcript building process, particularly on the protein level, is rarely performed if ever. To test and improve the quality of the automated transcriptome reconstruction, we used manually defined and curated genes, several of them experimentally validated. Several approaches to transcript construction were utilized, based on the available data: a draft genome, high quality RNAseq reads, and ESTs. In order to maximize the contribution of the various data, we integrated methods including de novo and genome based assembly, as well as EST clustering. After each step a set of manually curated genes was used for quality assessment of the transcripts. The interplay between the automated pipeline and the quality control indicated which additional processes were required to improve the transcriptome reconstruction. We discovered that E. huxleyi has a very high percentage of non-canonical splice junctions, and relatively high rates of intron retention, which caused unique issues with the currently available tools. While individual tools missed genes and artificially joined overlapping transcripts, combining the results of several tools improved the completeness and quality considerably. The final collection, created from the integration of several quality control and improvement rounds, was compared to the manually defined set both on the DNA and protein levels, and resulted in an improvement of 20% versus any of the read-based approaches alone. To the best of our knowledge, this is the first time that an automated transcript definition is subjected to quality control using manually defined and curated genes and thereafter the process is improved. We recommend using a set of manually curated genes to troubleshoot transcriptome reconstruction.

Listeria monocytogenes differential transcriptome analysis reveals temperature-dependent Agr regulation and suggests overlaps with other regulons.

PubMed

Garmyn, Dominique; Augagneur, Yoann; Gal, Laurent; Vivant, Anne-Laure; Piveteau, Pascal

2012-01-01

Listeria monocytogenes is a ubiquitous, opportunistic pathogenic organism. Environmental adaptation requires constant regulation of gene expression. Among transcriptional regulators, AgrA is part of an auto-induction system. Temperature is an environmental cue critical for in vivo adaptation. In order to investigate how temperature may affect AgrA-dependent transcription, we compared the transcriptomes of the parental strain L. monocytogenes EGD-e and its ΔagrA mutant at the saprophytic temperature of 25°C and in vivo temperature of 37°C. Variations of transcriptome were higher at 37°C than at 25°C. Results suggested that AgrA may be involved in the regulation of nitrogen transport, amino acids, purine and pyrimidine biosynthetic pathways and phage-related functions. Deregulations resulted in a growth advantage at 37°C, but affected salt tolerance. Finally, our results suggest overlaps with PrfA, σB, σH and CodY regulons. These overlaps may suggest that through AgrA, Listeria monocytogenes integrates information on its biotic environment.

Listeria monocytogenes Differential Transcriptome Analysis Reveals Temperature-Dependent Agr Regulation and Suggests Overlaps with Other Regulons

PubMed Central

Garmyn, Dominique; Augagneur, Yoann; Gal, Laurent; Vivant, Anne-Laure; Piveteau, Pascal

2012-01-01

Listeria monocytogenes is a ubiquitous, opportunistic pathogenic organism. Environmental adaptation requires constant regulation of gene expression. Among transcriptional regulators, AgrA is part of an auto-induction system. Temperature is an environmental cue critical for in vivo adaptation. In order to investigate how temperature may affect AgrA-dependent transcription, we compared the transcriptomes of the parental strain L. monocytogenes EGD-e and its ΔagrA mutant at the saprophytic temperature of 25°C and in vivo temperature of 37°C. Variations of transcriptome were higher at 37°C than at 25°C. Results suggested that AgrA may be involved in the regulation of nitrogen transport, amino acids, purine and pyrimidine biosynthetic pathways and phage-related functions. Deregulations resulted in a growth advantage at 37°C, but affected salt tolerance. Finally, our results suggest overlaps with PrfA, σB, σH and CodY regulons. These overlaps may suggest that through AgrA, Listeria monocytogenes integrates information on its biotic environment. PMID:23024744

Meta-analysis of pathway enrichment: combining independent and dependent omics data sets.

PubMed

Kaever, Alexander; Landesfeind, Manuel; Feussner, Kirstin; Morgenstern, Burkhard; Feussner, Ivo; Meinicke, Peter

2014-01-01

A major challenge in current systems biology is the combination and integrative analysis of large data sets obtained from different high-throughput omics platforms, such as mass spectrometry based Metabolomics and Proteomics or DNA microarray or RNA-seq-based Transcriptomics. Especially in the case of non-targeted Metabolomics experiments, where it is often impossible to unambiguously map ion features from mass spectrometry analysis to metabolites, the integration of more reliable omics technologies is highly desirable. A popular method for the knowledge-based interpretation of single data sets is the (Gene) Set Enrichment Analysis. In order to combine the results from different analyses, we introduce a methodical framework for the meta-analysis of p-values obtained from Pathway Enrichment Analysis (Set Enrichment Analysis based on pathways) of multiple dependent or independent data sets from different omics platforms. For dependent data sets, e.g. obtained from the same biological samples, the framework utilizes a covariance estimation procedure based on the nonsignificant pathways in single data set enrichment analysis. The framework is evaluated and applied in the joint analysis of Metabolomics mass spectrometry and Transcriptomics DNA microarray data in the context of plant wounding. In extensive studies of simulated data set dependence, the introduced correlation could be fully reconstructed by means of the covariance estimation based on pathway enrichment. By restricting the range of p-values of pathways considered in the estimation, the overestimation of correlation, which is introduced by the significant pathways, could be reduced. When applying the proposed methods to the real data sets, the meta-analysis was shown not only to be a powerful tool to investigate the correlation between different data sets and summarize the results of multiple analyses but also to distinguish experiment-specific key pathways.

Transcriptome profiling in engrailed-2 mutant mice reveals common molecular pathways associated with autism spectrum disorders.

PubMed

Sgadò, Paola; Provenzano, Giovanni; Dassi, Erik; Adami, Valentina; Zunino, Giulia; Genovesi, Sacha; Casarosa, Simona; Bozzi, Yuri

2013-12-19

Transcriptome analysis has been used in autism spectrum disorder (ASD) to unravel common pathogenic pathways based on the assumption that distinct rare genetic variants or epigenetic modifications affect common biological pathways. To unravel recurrent ASD-related neuropathological mechanisms, we took advantage of the En2-/- mouse model and performed transcriptome profiling on cerebellar and hippocampal adult tissues. Cerebellar and hippocampal tissue samples from three En2-/- and wild type (WT) littermate mice were assessed for differential gene expression using microarray hybridization followed by RankProd analysis. To identify functional categories overrepresented in the differentially expressed genes, we used integrated gene-network analysis, gene ontology enrichment and mouse phenotype ontology analysis. Furthermore, we performed direct enrichment analysis of ASD-associated genes from the SFARI repository in our differentially expressed genes. Given the limited number of animals used in the study, we used permissive criteria and identified 842 differentially expressed genes in En2-/- cerebellum and 862 in the En2-/- hippocampus. Our functional analysis revealed that the molecular signature of En2-/- cerebellum and hippocampus shares convergent pathological pathways with ASD, including abnormal synaptic transmission, altered developmental processes and increased immune response. Furthermore, when directly compared to the repository of the SFARI database, our differentially expressed genes in the hippocampus showed enrichment of ASD-associated genes significantly higher than previously reported. qPCR was performed for representative genes to confirm relative transcript levels compared to those detected in microarrays. Despite the limited number of animals used in the study, our bioinformatic analysis indicates the En2-/- mouse is a valuable tool for investigating molecular alterations related to ASD.

Comparative transcriptome analysis reveals carbohydrate and lipid metabolism blocks in Brassica napus L. male sterility induced by the chemical hybridization agent monosulfuron ester sodium.

PubMed

Li, Zhanjie; Cheng, Yufeng; Cui, Jianmin; Zhang, Peipei; Zhao, Huixian; Hu, Shengwu

2015-03-17

Chemical hybridization agents (CHAs) are often used to induce male sterility for the production of hybrid seeds. We previously discovered that monosulfuron ester sodium (MES), an acetolactate synthase (ALS) inhibitor of the herbicide sulfonylurea family, can induce rapeseed (Brassica napus L.) male sterility at approximately 1% concentration required for its herbicidal activity. To find some clues to the mechanism of MES inducing male sterility, the ultrastructural cytology observations, comparative transcriptome analysis, and physiological analysis on carbohydrate content were carried out in leaves and anthers at different developmental stages between the MES-treated and mock-treated rapeseed plants. Cytological analysis revealed that the plastid ultrastructure was abnormal in pollen mother cells and tapetal cells in male sterility anthers induced by MES treatment, with less material accumulation in it. However, starch granules were observed in chloroplastids of the epidermis cells in male sterility anthers. Comparative transcriptome analysis identified 1501 differentially expressed transcripts (DETs) in leaves and anthers at different developmental stages, most of these DETs being localized in plastid and mitochondrion. Transcripts involved in metabolism, especially in carbohydrate and lipid metabolism, and cellular transport were differentially expressed. Pathway visualization showed that the tightly regulated gene network for metabolism was reprogrammed to respond to MES treatment. The results of cytological observation and transcriptome analysis in the MES-treated rapeseed plants were mirrored by carbohydrate content analysis. MES treatment led to decrease in soluble sugars content in leaves and early stage buds, but increase in soluble sugars content and decrease in starch content in middle stage buds. Our integrative results suggested that carbohydrate and lipid metabolism were influenced by CHA-MES treatment during rapeseed anther development, which might responsible for low concentration MES specifically inducing male sterility. A simple action model of CHA-MES inducing male sterility in B. napus was proposed. These results will help us to understand the mechanism of MES inducing male sterility at low concentration, and might provide some potential targets for developing new male sterility inducing CHAs and for genetic manipulation in rapeseed breeding.

Changes in the transcriptomic profiles of maize roots in response to iron-deficiency stress.

PubMed

Li, Yan; Wang, Nian; Zhao, Fengtao; Song, Xuejiao; Yin, Zhaohua; Huang, Rong; Zhang, Chunqing

2014-07-01

Plants are often subjected to iron (Fe)-deficiency stress because of its low solubility. Plants have evolved two distinct strategies to solubilize and transport Fe to acclimate to this abiotic stress condition. Transcriptomic profiling analysis was performed using Illumina digital gene expression to understand the mechanism underlying resistance responses of roots to Fe starvation in maize, an important Strategy II plant. A total of 3,427, 4,069, 4,881, and 2,610 genes had significantly changed expression levels after Fe-deficiency treatments of 1, 2, 4 or 7 days, respectively. Genes involved in 2'-deoxymugineic acid (DMA) synthesis, secretion, and Fe(III)-DMA uptake were significantly induced. Many genes related to plant hormones, protein kinases, and protein phosphatases responded to Fe-deficiency stress, suggesting their regulatory roles in response to the Fe-deficiency stress. Functional annotation clustering analysis, using the Database for Annotation, Visualization and Integrated Discovery, revealed maize root responses to Fe starvation. This resulted in 38 functional annotation clusters: 25 for up-regulated genes, and 13 for down-regulated ones. These included genes encoding enzymes involved in the metabolism of carboxylic acids, isoprenoids and aromatic compounds, transporters, and stress response proteins. Our work provides integrated information for understanding maize response to Fe-deficiency stress.

Unraveling Molecular Signatures of Immunostimulatory Adjuvants in the Female Genital Tract through Systems Biology

PubMed Central

Brinkenberg, Ingrid; Samuelson, Emma; Thörn, Karolina; Nielsen, Jens; Harandi, Ali M.

2011-01-01

Sexually transmitted infections (STIs) unequivocally represent a major public health concern in both industrialized and developing countries. Previous efforts to develop vaccines for systemic immunization against a large number of STIs in humans have been unsuccessful. There is currently a drive to develop mucosal vaccines and adjuvants for delivery through the genital tract to confer protective immunity against STIs. Identification of molecular signatures that can be used as biomarkers for adjuvant potency can inform rational development of potent mucosal adjuvants. Here, we used systems biology to study global gene expression and signature molecules and pathways in the mouse vagina after treatment with two classes of experimental adjuvants. The Toll-like receptor 9 agonist CpG ODN and the invariant natural killer T cell agonist alpha-galactosylceramide, which we previously identified as equally potent vaginal adjuvants, were selected for this study. Our integrated analysis of genome-wide transcriptome data determined which signature pathways, processes and networks are shared by or otherwise exclusive to these 2 classes of experimental vaginal adjuvants in the mouse vagina. To our knowledge, this is the first integrated genome-wide transcriptome analysis of the effects of immunomodulatory adjuvants on the female genital tract of a mammal. These results could inform rational development of effective mucosal adjuvants for vaccination against STIs. PMID:21666746

Plant stress biomarkers from biosimulations: the Transcriptome-To-Metabolome (TTM) technology - effects of drought stress on rice.

PubMed

Phelix, C F; Feltus, F A

2015-01-01

Measuring biomarkers from plant tissue samples is challenging and expensive when the desire is to integrate transcriptomics, fluxomics, metabolomics, lipidomics, proteomics, physiomics and phenomics. We present a computational biology method where only the transcriptome needs to be measured and is used to derive a set of parameters for deterministic kinetic models of metabolic pathways. The technology is called Transcriptome-To-Metabolome (TTM) biosimulations, currently under commercial development, but available for non-commercial use by researchers. The simulated results on metabolites of 30 primary and secondary metabolic pathways in rice (Oryza sativa) were used as the biomarkers to predict whether the transcriptome was from a plant that had been under drought conditions. The rice transcriptomes were accessed from public archives and each individual plant was simulated. This unique quality of the TTM technology allows standard analyses on biomarker assessments, i.e. sensitivity, specificity, positive and negative predictive values, accuracy, receiver operator characteristics (ROC) curve and area under the ROC curve (AUC). Two validation methods were also used, the holdout and 10-fold cross validations. Initially 17 metabolites were identified as candidate biomarkers based on either statistical significance on binary phenotype when compared with control samples or recognition from the literature. The top three biomarkers based on AUC were gibberellic acid 12 (0.89), trehalose (0.80) and sn1-palmitate-sn2-oleic-phosphatidylglycerol (0.70). Neither heat map analyses of transcriptomes nor all 300 metabolites clustered the stressed and control groups effectively. The TTM technology allows the emergent properties of the integrated system to generate unique and useful 'Omics' information. © 2014 German Botanical Society and The Royal Botanical Society of the Netherlands.

Integrating Transcriptomics with Metabolic Modeling Predicts Biomarkers and Drug Targets for Alzheimer's Disease

PubMed Central

Stempler, Shiri; Yizhak, Keren; Ruppin, Eytan

2014-01-01

Accumulating evidence links numerous abnormalities in cerebral metabolism with the progression of Alzheimer's disease (AD), beginning in its early stages. Here, we integrate transcriptomic data from AD patients with a genome-scale computational human metabolic model to characterize the altered metabolism in AD, and employ state-of-the-art metabolic modelling methods to predict metabolic biomarkers and drug targets in AD. The metabolic descriptions derived are first tested and validated on a large scale versus existing AD proteomics and metabolomics data. Our analysis shows a significant decrease in the activity of several key metabolic pathways, including the carnitine shuttle, folate metabolism and mitochondrial transport. We predict several metabolic biomarkers of AD progression in the blood and the CSF, including succinate and prostaglandin D2. Vitamin D and steroid metabolism pathways are enriched with predicted drug targets that could mitigate the metabolic alterations observed. Taken together, this study provides the first network wide view of the metabolic alterations associated with AD progression. Most importantly, it offers a cohort of new metabolic leads for the diagnosis of AD and its treatment. PMID:25127241

Transcriptator: An Automated Computational Pipeline to Annotate Assembled Reads and Identify Non Coding RNA.

PubMed

Tripathi, Kumar Parijat; Evangelista, Daniela; Zuccaro, Antonio; Guarracino, Mario Rosario

2015-01-01

RNA-seq is a new tool to measure RNA transcript counts, using high-throughput sequencing at an extraordinary accuracy. It provides quantitative means to explore the transcriptome of an organism of interest. However, interpreting this extremely large data into biological knowledge is a problem, and biologist-friendly tools are lacking. In our lab, we developed Transcriptator, a web application based on a computational Python pipeline with a user-friendly Java interface. This pipeline uses the web services available for BLAST (Basis Local Search Alignment Tool), QuickGO and DAVID (Database for Annotation, Visualization and Integrated Discovery) tools. It offers a report on statistical analysis of functional and Gene Ontology (GO) annotation's enrichment. It helps users to identify enriched biological themes, particularly GO terms, pathways, domains, gene/proteins features and protein-protein interactions related informations. It clusters the transcripts based on functional annotations and generates a tabular report for functional and gene ontology annotations for each submitted transcript to the web server. The implementation of QuickGo web-services in our pipeline enable the users to carry out GO-Slim analysis, whereas the integration of PORTRAIT (Prediction of transcriptomic non coding RNA (ncRNA) by ab initio methods) helps to identify the non coding RNAs and their regulatory role in transcriptome. In summary, Transcriptator is a useful software for both NGS and array data. It helps the users to characterize the de-novo assembled reads, obtained from NGS experiments for non-referenced organisms, while it also performs the functional enrichment analysis of differentially expressed transcripts/genes for both RNA-seq and micro-array experiments. It generates easy to read tables and interactive charts for better understanding of the data. The pipeline is modular in nature, and provides an opportunity to add new plugins in the future. Web application is freely available at: http://www-labgtp.na.icar.cnr.it/Transcriptator.

Unique mechanisms of sheng yu decoction ( shèng yù tang) on ischemic stroke mice revealed by an integrated neurofunctional and transcriptome analysis.

PubMed

Hou, Yu-Chang; Lu, Chung-Kuang; Wang, Yea-Hwey; Chern, Chang-Ming; Liou, Kuo-Tong; Wang, Hsei-Wei; Shen, Yuh-Chiang

2013-10-01

Sheng Yu Decoction ( Shèng Yù Tang; SYD) is a popular traditional Chinese medicine (TCM) remedy used in treating cardiovascular and brain-related dysfunction clinically; yet, its neuroprotective mechanisms are still unclear. Here, mice were subjected to an acute ischemic stroke to examine the efficacy and mechanisms of action of SYD by an integrated neurofunctional and transcriptome analysis. More than 80% of the mice died within 2 days after ischemic stroke with vehicle treatment. Treatments with SYD (1.0 g/kg, twice daily, orally or p.o.) and recombinant thrombolytic tissue plasminogen activator (rt-PA; 10 mg/kg, once daily, intravenously or i.v.) both significantly extended the lifespan as compared to that of the vehicle-treated stroke group. SYD successfully restored brain function, ameliorated cerebral infarction and oxidative stress, and significantly improved neurological deficits in mice with stroke. Molecular impact of SYD by a genome-wide transcriptome analysis using brains from stroke mice showed a total of 162 out of 2081 ischemia-induced probe sets were significantly influenced by SYD. Mining the functional modules and genetic networks of these 162 genes revealed a significant upregulation of neuroprotective genes in Wnt receptor signaling pathway (3 genes) and regulation of cell communication (7 genes) and downregulation of destructive genes in response to stress (13 genes) and in the induction of inflammation (5 genes), cytokine production (4 genes), angiogenesis (3 genes), vasculature (6 genes) and blood vessel (5 genes) development, wound healing (7 genes), defense response (7 genes), chemotaxis (4 genes), immune response (7 genes), antigen processing and presenting (3 genes), and leukocyte-mediated cytotoxicity (2 genes) by SYD. Our results suggest that SYD could protect mice against ischemic stroke primarily through significantly downregulating the damaging genes involved in stress, inflammation, angiogenesis, blood vessel formation, immune responses, and wound healing, as well as upregulating the genes mediating neurogenesis and cell communication, which make SYD beneficial for treating ischemic stroke.

The low-abundance transcriptome reveals novel biomarkers, specific intracellular pathways and targetable genes associated with advanced gastric cancer.

PubMed

Bizama, Carolina; Benavente, Felipe; Salvatierra, Edgardo; Gutiérrez-Moraga, Ana; Espinoza, Jaime A; Fernández, Elmer A; Roa, Iván; Mazzolini, Guillermo; Sagredo, Eduardo A; Gidekel, Manuel; Podhajcer, Osvaldo L

2014-02-15

Studies on the low-abundance transcriptome are of paramount importance for identifying the intimate mechanisms of tumor progression that can lead to novel therapies. The aim of the present study was to identify novel markers and targetable genes and pathways in advanced human gastric cancer through analyses of the low-abundance transcriptome. The procedure involved an initial subtractive hybridization step, followed by global gene expression analysis using microarrays. We observed profound differences, both at the single gene and gene ontology levels, between the low-abundance transcriptome and the whole transcriptome. Analysis of the low-abundance transcriptome led to the identification and validation by tissue microarrays of novel biomarkers, such as LAMA3 and TTN; moreover, we identified cancer type-specific intracellular pathways and targetable genes, such as IRS2, IL17, IFNγ, VEGF-C, WISP1, FZD5 and CTBP1 that were not detectable by whole transcriptome analyses. We also demonstrated that knocking down the expression of CTBP1 sensitized gastric cancer cells to mainstay chemotherapeutic drugs. We conclude that the analysis of the low-abundance transcriptome provides useful insights into the molecular basis and treatment of cancer. © 2013 UICC.

Integrated transcriptomic and proteomic evaluation of gentamicin nephrotoxicity in rats

DOE Office of Scientific and Technical Information (OSTI.GOV)

Com, Emmanuelle, E-mail: emmanuelle.com@univ-rennes1.fr; INSERM U625, Proteomics Core Facility Biogenouest, Rennes; Boitier, Eric

2012-01-01

Gentamicin is an aminoglycoside antibiotic, which induces renal tubular necrosis in rats. In the context of the European InnoMed PredTox project, transcriptomic and proteomic studies were performed to provide new insights into the molecular mechanisms of gentamicin-induced nephrotoxicity. Male Wistar rats were treated with 25 and 75 mg/kg/day subcutaneously for 1, 3 and 14 days. Histopathology observations showed mild tubular degeneration/necrosis and regeneration and moderate mononuclear cell infiltrate after long-term treatment. Transcriptomic data indicated a strong treatment-related gene expression modulation in kidney and blood cells at the high dose after 14 days of treatment, with the regulation of 463 andmore » 3241 genes, respectively. Of note, the induction of NF-kappa B pathway via the p38 MAPK cascade in the kidney, together with the activation of T-cell receptor signaling in blood cells were suggestive of inflammatory processes in relation with the recruitment of mononuclear cells in the kidney. Proteomic results showed a regulation of 163 proteins in kidney at the high dose after 14 days of treatment. These protein modulations were suggestive of a mitochondrial dysfunction with impairment of cellular energy production, induction of oxidative stress, an effect on protein biosynthesis and on cellular assembly and organization. Proteomic results also provided clues for potential nephrotoxicity biomarkers such as AGAT and PRBP4 which were strongly modulated in the kidney. Transcriptomic and proteomic data turned out to be complementary and their integration gave a more comprehensive insight into the putative mode of nephrotoxicity of gentamicin which was in accordance with histopathological findings. -- Highlights: ► Gentamicin induces renal tubular necrosis in rats. ► The mechanisms of gentamicin nephrotoxicity remain still elusive. ► Transcriptomic and proteomic analyses were performed to study this toxicity in rats. ► Transcriptomic and proteomic data turned out to be complementary and are integrated. ► A more comprehensive putative model of nephrotoxicity of gentamicin is presented.« less

Reconstructing genome-wide regulatory network of E. coli using transcriptome data and predicted transcription factor activities

PubMed Central

2011-01-01

Background Gene regulatory networks play essential roles in living organisms to control growth, keep internal metabolism running and respond to external environmental changes. Understanding the connections and the activity levels of regulators is important for the research of gene regulatory networks. While relevance score based algorithms that reconstruct gene regulatory networks from transcriptome data can infer genome-wide gene regulatory networks, they are unfortunately prone to false positive results. Transcription factor activities (TFAs) quantitatively reflect the ability of the transcription factor to regulate target genes. However, classic relevance score based gene regulatory network reconstruction algorithms use models do not include the TFA layer, thus missing a key regulatory element. Results This work integrates TFA prediction algorithms with relevance score based network reconstruction algorithms to reconstruct gene regulatory networks with improved accuracy over classic relevance score based algorithms. This method is called Gene expression and Transcription factor activity based Relevance Network (GTRNetwork). Different combinations of TFA prediction algorithms and relevance score functions have been applied to find the most efficient combination. When the integrated GTRNetwork method was applied to E. coli data, the reconstructed genome-wide gene regulatory network predicted 381 new regulatory links. This reconstructed gene regulatory network including the predicted new regulatory links show promising biological significances. Many of the new links are verified by known TF binding site information, and many other links can be verified from the literature and databases such as EcoCyc. The reconstructed gene regulatory network is applied to a recent transcriptome analysis of E. coli during isobutanol stress. In addition to the 16 significantly changed TFAs detected in the original paper, another 7 significantly changed TFAs have been detected by using our reconstructed network. Conclusions The GTRNetwork algorithm introduces the hidden layer TFA into classic relevance score-based gene regulatory network reconstruction processes. Integrating the TFA biological information with regulatory network reconstruction algorithms significantly improves both detection of new links and reduces that rate of false positives. The application of GTRNetwork on E. coli gene transcriptome data gives a set of potential regulatory links with promising biological significance for isobutanol stress and other conditions. PMID:21668997

Integration of deep transcriptome and proteome analyses reveals the components of alkaloid metabolism in opium poppy cell cultures

PubMed Central

2010-01-01

Background Papaver somniferum (opium poppy) is the source for several pharmaceutical benzylisoquinoline alkaloids including morphine, the codeine and sanguinarine. In response to treatment with a fungal elicitor, the biosynthesis and accumulation of sanguinarine is induced along with other plant defense responses in opium poppy cell cultures. The transcriptional induction of alkaloid metabolism in cultured cells provides an opportunity to identify components of this process via the integration of deep transcriptome and proteome databases generated using next-generation technologies. Results A cDNA library was prepared for opium poppy cell cultures treated with a fungal elicitor for 10 h. Using 454 GS-FLX Titanium pyrosequencing, 427,369 expressed sequence tags (ESTs) with an average length of 462 bp were generated. Assembly of these sequences yielded 93,723 unigenes, of which 23,753 were assigned Gene Ontology annotations. Transcripts encoding all known sanguinarine biosynthetic enzymes were identified in the EST database, 5 of which were represented among the 50 most abundant transcripts. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) of total protein extracts from cell cultures treated with a fungal elicitor for 50 h facilitated the identification of 1,004 proteins. Proteins were fractionated by one-dimensional SDS-PAGE and digested with trypsin prior to LC-MS/MS analysis. Query of an opium poppy-specific EST database substantially enhanced peptide identification. Eight out of 10 known sanguinarine biosynthetic enzymes and many relevant primary metabolic enzymes were represented in the peptide database. Conclusions The integration of deep transcriptome and proteome analyses provides an effective platform to catalogue the components of secondary metabolism, and to identify genes encoding uncharacterized enzymes. The establishment of corresponding transcript and protein databases generated by next-generation technologies in a system with a well-defined metabolite profile facilitates an improved linkage between genes, enzymes, and pathway components. The proteome database represents the most relevant alkaloid-producing enzymes, compared with the much deeper and more complete transcriptome library. The transcript database contained full-length mRNAs encoding most alkaloid biosynthetic enzymes, which is a key requirement for the functional characterization of novel gene candidates. PMID:21083930

Transcriptome assembly and digital gene expression atlas of the rainbow trout

USDA-ARS?s Scientific Manuscript database

Background: Transcriptome analysis is a preferred method for gene discovery, marker development and gene expression profiling in non-model organisms. Previously, we sequenced a transcriptome reference using Sanger-based and 454-pyrosequencing, however, a transcriptome assembly is still incomplete an...

Preliminary profiling of blood transcriptome in a rat model of hemorrhagic shock.

PubMed

Braga, D; Barcella, M; D'Avila, F; Lupoli, S; Tagliaferri, F; Santamaria, M H; DeLano, F A; Baselli, G; Schmid-Schönbein, G W; Kistler, E B; Aletti, F; Barlassina, C

2017-08-01

Hemorrhagic shock is a leading cause of morbidity and mortality worldwide. Significant blood loss may lead to decreased blood pressure and inadequate tissue perfusion with resultant organ failure and death, even after replacement of lost blood volume. One reason for this high acuity is that the fundamental mechanisms of shock are poorly understood. Proteomic and metabolomic approaches have been used to investigate the molecular events occurring in hemorrhagic shock but, to our knowledge, a systematic analysis of the transcriptomic profile is missing. Therefore, a pilot analysis using paired-end RNA sequencing was used to identify changes that occur in the blood transcriptome of rats subjected to hemorrhagic shock after blood reinfusion. Hemorrhagic shock was induced using a Wigger's shock model. The transcriptome of whole blood from shocked animals shows modulation of genes related to inflammation and immune response (Tlr13, Il1b, Ccl6, Lgals3), antioxidant functions (Mt2A, Mt1), tissue injury and repair pathways (Gpnmb, Trim72) and lipid mediators (Alox5ap, Ltb4r, Ptger2) compared with control animals. These findings are congruent with results obtained in hemorrhagic shock analysis by other authors using metabolomics and proteomics. The analysis of blood transcriptome may be a valuable tool to understand the biological changes occurring in hemorrhagic shock and a promising approach for the identification of novel biomarkers and therapeutic targets. Impact statement This study provides the first pilot analysis of the changes occurring in transcriptome expression of whole blood in hemorrhagic shock (HS) rats. We showed that the analysis of blood transcriptome is a useful approach to investigate pathways and functional alterations in this disease condition. This pilot study encourages the possible application of transcriptome analysis in the clinical setting, for the molecular profiling of whole blood in HS patients.

RNAseq versus genome-predicted transcriptomes: a large population of novel transcripts identified in an Illumina-454 Hydra transcriptome.

PubMed

Wenger, Yvan; Galliot, Brigitte

2013-03-25

Evolutionary studies benefit from deep sequencing technologies that generate genomic and transcriptomic sequences from a variety of organisms. Genome sequencing and RNAseq have complementary strengths. In this study, we present the assembly of the most complete Hydra transcriptome to date along with a comparative analysis of the specific features of RNAseq and genome-predicted transcriptomes currently available in the freshwater hydrozoan Hydra vulgaris. To produce an accurate and extensive Hydra transcriptome, we combined Illumina and 454 Titanium reads, giving the primacy to Illumina over 454 reads to correct homopolymer errors. This strategy yielded an RNAseq transcriptome that contains 48'909 unique sequences including splice variants, representing approximately 24'450 distinct genes. Comparative analysis to the available genome-predicted transcriptomes identified 10'597 novel Hydra transcripts that encode 529 evolutionarily-conserved proteins. The annotation of 170 human orthologs points to critical functions in protein biosynthesis, FGF and TOR signaling, vesicle transport, immunity, cell cycle regulation, cell death, mitochondrial metabolism, transcription and chromatin regulation. However, a majority of these novel transcripts encodes short ORFs, at least 767 of them corresponding to pseudogenes. This RNAseq transcriptome also lacks 11'270 predicted transcripts that correspond either to silent genes or to genes expressed below the detection level of this study. We established a simple and powerful strategy to combine Illumina and 454 reads and we produced, with genome assistance, an extensive and accurate Hydra transcriptome. The comparative analysis of the RNAseq transcriptome with genome-predicted transcriptomes lead to the identification of large populations of novel as well as missing transcripts that might reflect Hydra-specific evolutionary events.

RNAseq versus genome-predicted transcriptomes: a large population of novel transcripts identified in an Illumina-454 Hydra transcriptome

PubMed Central

2013-01-01

Background Evolutionary studies benefit from deep sequencing technologies that generate genomic and transcriptomic sequences from a variety of organisms. Genome sequencing and RNAseq have complementary strengths. In this study, we present the assembly of the most complete Hydra transcriptome to date along with a comparative analysis of the specific features of RNAseq and genome-predicted transcriptomes currently available in the freshwater hydrozoan Hydra vulgaris. Results To produce an accurate and extensive Hydra transcriptome, we combined Illumina and 454 Titanium reads, giving the primacy to Illumina over 454 reads to correct homopolymer errors. This strategy yielded an RNAseq transcriptome that contains 48’909 unique sequences including splice variants, representing approximately 24’450 distinct genes. Comparative analysis to the available genome-predicted transcriptomes identified 10’597 novel Hydra transcripts that encode 529 evolutionarily-conserved proteins. The annotation of 170 human orthologs points to critical functions in protein biosynthesis, FGF and TOR signaling, vesicle transport, immunity, cell cycle regulation, cell death, mitochondrial metabolism, transcription and chromatin regulation. However, a majority of these novel transcripts encodes short ORFs, at least 767 of them corresponding to pseudogenes. This RNAseq transcriptome also lacks 11’270 predicted transcripts that correspond either to silent genes or to genes expressed below the detection level of this study. Conclusions We established a simple and powerful strategy to combine Illumina and 454 reads and we produced, with genome assistance, an extensive and accurate Hydra transcriptome. The comparative analysis of the RNAseq transcriptome with genome-predicted transcriptomes lead to the identification of large populations of novel as well as missing transcripts that might reflect Hydra-specific evolutionary events. PMID:23530871

Integrative transcriptome analysis identifies deregulated microRNA-transcription factor networks in lung adenocarcinoma

PubMed Central

Cinegaglia, Naiara C.; Andrade, Sonia Cristina S.; Tokar, Tomas; Pinheiro, Maísa; Severino, Fábio E.; Oliveira, Rogério A.; Hasimoto, Erica N.; Cataneo, Daniele C.; Cataneo, Antônio J.M.; Defaveri, Júlio; Souza, Cristiano P.; Marques, Márcia M.C.; Carvalho, Robson F.; Coutinho, Luiz L.; Gross, Jefferson L.; Rogatto, Silvia R.; Lam, Wan L.; Jurisica, Igor; Reis, Patricia P.

2016-01-01

Herein, we aimed at identifying global transcriptome microRNA (miRNA) changes and miRNA target genes in lung adenocarcinoma. Samples were selected as training (N = 24) and independent validation (N = 34) sets. Tissues were microdissected to obtain >90% tumor or normal lung cells, subjected to miRNA transcriptome sequencing and TaqMan quantitative PCR validation. We further integrated our data with published miRNA and mRNA expression datasets across 1,491 lung adenocarcinoma and 455 normal lung samples. We identified known and novel, significantly over- and under-expressed (p ≤ 0.01 and FDR≤0.1) miRNAs in lung adenocarcinoma compared to normal lung tissue: let-7a, miR-10a, miR-15b, miR-23b, miR-26a, miR-26b, miR-29a, miR-30e, miR-99a, miR-146b, miR-181b, miR-181c, miR-421, miR-181a, miR-574 and miR-1247. Validated miRNAs included let-7a-2, let-7a-3, miR-15b, miR-21, miR-155 and miR-200b; higher levels of miR-21 expression were associated with lower patient survival (p = 0.042). We identified a regulatory network including miR-15b and miR-155, and transcription factors with prognostic value in lung cancer. Our findings may contribute to the development of treatment strategies in lung adenocarcinoma. PMID:27081085

Integrating transcriptome and genome re-sequencing data to identify key genes and mutations affecting chicken eggshell qualities.

PubMed

Zhang, Quan; Zhu, Feng; Liu, Long; Zheng, Chuan Wei; Wang, De He; Hou, Zhuo Cheng; Ning, Zhong Hua

2015-01-01

Eggshell damages lead to economic losses in the egg production industry and are a threat to human health. We examined 49-wk-old Rhode Island White hens (Gallus gallus) that laid eggs having shells with significantly different strengths and thicknesses. We used HiSeq 2000 (Illumina) sequencing to characterize the chicken transcriptome and whole genome to identify the key genes and genetic mutations associated with eggshell calcification. We identified a total of 14,234 genes expressed in the chicken uterus, representing 89% of all annotated chicken genes. A total of 889 differentially expressed genes were identified by comparing low eggshell strength (LES) and normal eggshell strength (NES) genomes. The DEGs are enriched in calcification-related processes, including calcium ion transport and calcium signaling pathways as revealed by gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) pathway analysis. Some important matrix proteins, such as OC-116, LTF and SPP1, were also expressed differentially between two groups. A total of 3,671,919 single-nucleotide polymorphisms (SNPs) and 508,035 Indels were detected in protein coding genes by whole-genome re-sequencing, including 1775 non-synonymous variations and 19 frame-shift Indels in DEGs. SNPs and Indels found in this study could be further investigated for eggshell traits. This is the first report to integrate the transcriptome and genome re-sequencing to target the genetic variations which decreased the eggshell qualities. These findings further advance our understanding of eggshell calcification in the chicken uterus.

Poplar trees reconfigure the transcriptome and metabolome in response to drought in a genotype- and time-of-day-dependent manner.

PubMed

Hamanishi, Erin T; Barchet, Genoa L H; Dauwe, Rebecca; Mansfield, Shawn D; Campbell, Malcolm M

2015-04-21

Drought has a major impact on tree growth and survival. Understanding tree responses to this stress can have important application in both conservation of forest health, and in production forestry. Trees of the genus Populus provide an excellent opportunity to explore the mechanistic underpinnings of forest tree drought responses, given the growing molecular resources that are available for this taxon. Here, foliar tissue of six water-deficit stressed P. balsamifera genotypes was analysed for variation in the metabolome in response to drought and time of day by using an untargeted metabolite profiling technique, gas chromatography/mass-spectrometry (GC/MS). Significant variation in the metabolome was observed in response the imposition of water-deficit stress. Notably, organic acid intermediates such as succinic and malic acid had lower concentrations in leaves exposed to drought, whereas galactinol and raffinose were found in increased concentrations. A number of metabolites with significant difference in accumulation under water-deficit conditions exhibited intraspecific variation in metabolite accumulation. Large magnitude fold-change accumulation was observed in three of the six genotypes. In order to understand the interaction between the transcriptome and metabolome, an integrated analysis of the drought-responsive transcriptome and the metabolome was performed. One P. balsamifera genotype, AP-1006, demonstrated a lack of congruence between the magnitude of the drought transcriptome response and the magnitude of the metabolome response. More specifically, metabolite profiles in AP-1006 demonstrated the smallest changes in response to water-deficit conditions. Pathway analysis of the transcriptome and metabolome revealed specific genotypic responses with respect to primary sugar accumulation, citric acid metabolism, and raffinose family oligosaccharide biosynthesis. The intraspecific variation in the molecular strategies that underpin the responses to drought among genotypes may have an important role in the maintenance of forest health and productivity.

Integrated transcriptome catalogue and organ-specific profiling of gene expression in fertile garlic (Allium sativum L.).

PubMed

Kamenetsky, Rina; Faigenboim, Adi; Shemesh Mayer, Einat; Ben Michael, Tomer; Gershberg, Chen; Kimhi, Sagie; Esquira, Itzhak; Rohkin Shalom, Sarit; Eshel, Dani; Rabinowitch, Haim D; Sherman, Amir

2015-01-22

Garlic is cultivated and consumed worldwide as a popular condiment and green vegetable with medicinal and neutraceutical properties. Garlic cultivars do not produce seeds, and therefore, this plant has not been the subject of either classical breeding or genetic studies. However, recent achievements in fertility restoration in a number of genotypes have led to flowering and seed production, thus enabling genetic studies and breeding in garlic. A transcriptome catalogue of fertile garlic was produced from multiplexed gene libraries, using RNA collected from various plant organs, including inflorescences and flowers. Over 32 million 250-bp paired-end reads were assembled into an extensive transcriptome of 240,000 contigs. An abundant transcriptome assembled separately from 102,000 highly expressed contigs was annotated and analyzed for gene ontology and metabolic pathways. Organ-specific analysis showed significant variation of gene expression between plant organs, with the highest number of specific reads in inflorescences and flowers. Analysis of the enriched biological processes and molecular functions revealed characteristic patterns for stress response, flower development and photosynthetic activity. Orthologues of key flowering genes were differentially expressed, not only in reproductive tissues, but also in leaves and bulbs, suggesting their role in flower-signal transduction and the bulbing process. More than 100 variants and isoforms of enzymes involved in organosulfur metabolism were differentially expressed and had organ-specific patterns. In addition to plant genes, viral RNA of at least four garlic viruses was detected, mostly in the roots and cloves, whereas only 1-4% of the reads were found in the foliage leaves. The de novo transcriptome of fertile garlic represents a new resource for research and breeding of this important crop, as well as for the development of effective molecular markers for useful traits, including fertility and seed production, resistance to pests and neutraceutical characteristics.

Transcriptome comparison and gene coexpression network analysis provide a systems view of citrus response to ‘Candidatus Liberibacter asiaticus’ infection

PubMed Central

2013-01-01

Background Huanglongbing (HLB) is arguably the most destructive disease for the citrus industry. HLB is caused by infection of the bacterium, Candidatus Liberibacter spp. Several citrus GeneChip studies have revealed thousands of genes that are up- or down-regulated by infection with Ca. Liberibacter asiaticus. However, whether and how these host genes act to protect against HLB remains poorly understood. Results As a first step towards a mechanistic view of citrus in response to the HLB bacterial infection, we performed a comparative transcriptome analysis and found that a total of 21 Probesets are commonly up-regulated by the HLB bacterial infection. In addition, a number of genes are likely regulated specifically at early, late or very late stages of the infection. Furthermore, using Pearson correlation coefficient-based gene coexpression analysis, we constructed a citrus HLB response network consisting of 3,507 Probesets and 56,287 interactions. Genes involved in carbohydrate and nitrogen metabolic processes, transport, defense, signaling and hormone response were overrepresented in the HLB response network and the subnetworks for these processes were constructed. Analysis of the defense and hormone response subnetworks indicates that hormone response is interconnected with defense response. In addition, mapping the commonly up-regulated HLB responsive genes into the HLB response network resulted in a core subnetwork where transport plays a key role in the citrus response to the HLB bacterial infection. Moreover, analysis of a phloem protein subnetwork indicates a role for this protein and zinc transporters or zinc-binding proteins in the citrus HLB defense response. Conclusion Through integrating transcriptome comparison and gene coexpression network analysis, we have provided for the first time a systems view of citrus in response to the Ca. Liberibacter spp. infection causing HLB. PMID:23324561

Mechanism of cisplatin proximal tubule toxicity revealed by integrating transcriptomics, proteomics, metabolomics and biokinetics.

PubMed

Wilmes, Anja; Bielow, Chris; Ranninger, Christina; Bellwon, Patricia; Aschauer, Lydia; Limonciel, Alice; Chassaigne, Hubert; Kristl, Theresa; Aiche, Stephan; Huber, Christian G; Guillou, Claude; Hewitt, Philipp; Leonard, Martin O; Dekant, Wolfgang; Bois, Frederic; Jennings, Paul

2015-12-25

Cisplatin is one of the most widely used chemotherapeutic agents for the treatment of solid tumours. The major dose-limiting factor is nephrotoxicity, in particular in the proximal tubule. Here, we use an integrated omics approach, including transcriptomics, proteomics and metabolomics coupled to biokinetics to identify cell stress response pathways induced by cisplatin. The human renal proximal tubular cell line RPTEC/TERT1 was treated with sub-cytotoxic concentrations of cisplatin (0.5 and 2 μM) in a daily repeat dose treating regime for up to 14 days. Biokinetic analysis showed that cisplatin was taken up from the basolateral compartment, transported to the apical compartment, and accumulated in cells over time. This is in line with basolateral uptake of cisplatin via organic cation transporter 2 and bioactivation via gamma-glutamyl transpeptidase located on the apical side of proximal tubular cells. Cisplatin affected several pathways including, p53 signalling, Nrf2 mediated oxidative stress response, mitochondrial processes, mTOR and AMPK signalling. In addition, we identified novel pathways changed by cisplatin, including eIF2 signalling, actin nucleation via the ARP/WASP complex and regulation of cell polarization. In conclusion, using an integrated omic approach together with biokinetics we have identified both novel and established mechanisms of cisplatin toxicity. Copyright © 2014 Elsevier Ltd. All rights reserved.

Resources and Recommendations for Using Transcriptomics to Address Grand Challenges in Comparative Biology

PubMed Central

Mykles, Donald L.; Burnett, Karen G.; Durica, David S.; Joyce, Blake L.; McCarthy, Fiona M.; Schmidt, Carl J.; Stillman, Jonathon H.

2016-01-01

High-throughput RNA sequencing (RNA-seq) technology has become an important tool for studying physiological responses of organisms to changes in their environment. De novo assembly of RNA-seq data has allowed researchers to create a comprehensive catalog of genes expressed in a tissue and to quantify their expression without a complete genome sequence. The contributions from the “Tapping the Power of Crustacean Transcriptomics to Address Grand Challenges in Comparative Biology” symposium in this issue show the successes and limitations of using RNA-seq in the study of crustaceans. In conjunction with the symposium, the Animal Genome to Phenome Research Coordination Network collated comments from participants at the meeting regarding the challenges encountered when using transcriptomics in their research. Input came from novices and experts ranging from graduate students to principal investigators. Many were unaware of the bioinformatics analysis resources currently available on the CyVerse platform. Our analysis of community responses led to three recommendations for advancing the field: (1) integration of genomic and RNA-seq sequence assemblies for crustacean gene annotation and comparative expression; (2) development of methodologies for the functional analysis of genes; and (3) information and training exchange among laboratories for transmission of best practices. The field lacks the methods for manipulating tissue-specific gene expression. The decapod crustacean research community should consider the cherry shrimp, Neocaridina denticulata, as a decapod model for the application of transgenic tools for functional genomics. This would require a multi-investigator effort. PMID:27639274

An Approach to Function Annotation for Proteins of Unknown Function (PUFs) in the Transcriptome of Indian Mulberry.

PubMed

Dhanyalakshmi, K H; Naika, Mahantesha B N; Sajeevan, R S; Mathew, Oommen K; Shafi, K Mohamed; Sowdhamini, Ramanathan; N Nataraja, Karaba

2016-01-01

The modern sequencing technologies are generating large volumes of information at the transcriptome and genome level. Translation of this information into a biological meaning is far behind the race due to which a significant portion of proteins discovered remain as proteins of unknown function (PUFs). Attempts to uncover the functional significance of PUFs are limited due to lack of easy and high throughput functional annotation tools. Here, we report an approach to assign putative functions to PUFs, identified in the transcriptome of mulberry, a perennial tree commonly cultivated as host of silkworm. We utilized the mulberry PUFs generated from leaf tissues exposed to drought stress at whole plant level. A sequence and structure based computational analysis predicted the probable function of the PUFs. For rapid and easy annotation of PUFs, we developed an automated pipeline by integrating diverse bioinformatics tools, designated as PUFs Annotation Server (PUFAS), which also provides a web service API (Application Programming Interface) for a large-scale analysis up to a genome. The expression analysis of three selected PUFs annotated by the pipeline revealed abiotic stress responsiveness of the genes, and hence their potential role in stress acclimation pathways. The automated pipeline developed here could be extended to assign functions to PUFs from any organism in general. PUFAS web server is available at http://caps.ncbs.res.in/pufas/ and the web service is accessible at http://capservices.ncbs.res.in/help/pufas.

Predicted Arabidopsis Interactome Resource and Gene Set Linkage Analysis: A Transcriptomic Analysis Resource.

PubMed

Yao, Heng; Wang, Xiaoxuan; Chen, Pengcheng; Hai, Ling; Jin, Kang; Yao, Lixia; Mao, Chuanzao; Chen, Xin

2018-05-01

An advanced functional understanding of omics data is important for elucidating the design logic of physiological processes in plants and effectively controlling desired traits in plants. We present the latest versions of the Predicted Arabidopsis Interactome Resource (PAIR) and of the gene set linkage analysis (GSLA) tool, which enable the interpretation of an observed transcriptomic change (differentially expressed genes [DEGs]) in Arabidopsis ( Arabidopsis thaliana ) with respect to its functional impact for biological processes. PAIR version 5.0 integrates functional association data between genes in multiple forms and infers 335,301 putative functional interactions. GSLA relies on this high-confidence inferred functional association network to expand our perception of the functional impacts of an observed transcriptomic change. GSLA then interprets the biological significance of the observed DEGs using established biological concepts (annotation terms), describing not only the DEGs themselves but also their potential functional impacts. This unique analytical capability can help researchers gain deeper insights into their experimental results and highlight prospective directions for further investigation. We demonstrate the utility of GSLA with two case studies in which GSLA uncovered how molecular events may have caused physiological changes through their collective functional influence on biological processes. Furthermore, we showed that typical annotation-enrichment tools were unable to produce similar insights to PAIR/GSLA. The PAIR version 5.0-inferred interactome and GSLA Web tool both can be accessed at http://public.synergylab.cn/pair/. © 2018 American Society of Plant Biologists. All Rights Reserved.

The Urinary Bladder Transcriptome and Proteome Defined by Transcriptomics and Antibody-Based Profiling

PubMed Central

Habuka, Masato; Fagerberg, Linn; Hallström, Björn M.; Pontén, Fredrik; Yamamoto, Tadashi; Uhlen, Mathias

2015-01-01

To understand functions and diseases of urinary bladder, it is important to define its molecular constituents and their roles in urinary bladder biology. Here, we performed genome-wide deep RNA sequencing analysis of human urinary bladder samples and identified genes up-regulated in the urinary bladder by comparing the transcriptome data to those of all other major human tissue types. 90 protein-coding genes were elevated in the urinary bladder, either with enhanced expression uniquely in the urinary bladder or elevated expression together with at least one other tissue (group enriched). We further examined the localization of these proteins by immunohistochemistry and tissue microarrays and 20 of these 90 proteins were localized to the whole urothelium with a majority not yet described in the context of the urinary bladder. Four additional proteins were found specifically in the umbrella cells (Uroplakin 1a, 2, 3a, and 3b), and three in the intermediate/basal cells (KRT17, PCP4L1 and ATP1A4). 61 of the 90 elevated genes have not been previously described in the context of urinary bladder and the corresponding proteins are interesting targets for more in-depth studies. In summary, an integrated omics approach using transcriptomics and antibody-based profiling has been used to define a comprehensive list of proteins elevated in the urinary bladder. PMID:26694548

Microfluidics for genome-wide studies involving next generation sequencing

PubMed Central

Murphy, Travis W.; Lu, Chang

2017-01-01

Next-generation sequencing (NGS) has revolutionized how molecular biology studies are conducted. Its decreasing cost and increasing throughput permit profiling of genomic, transcriptomic, and epigenomic features for a wide range of applications. Microfluidics has been proven to be highly complementary to NGS technology with its unique capabilities for handling small volumes of samples and providing platforms for automation, integration, and multiplexing. In this article, we review recent progress on applying microfluidics to facilitate genome-wide studies. We emphasize on several technical aspects of NGS and how they benefit from coupling with microfluidic technology. We also summarize recent efforts on developing microfluidic technology for genomic, transcriptomic, and epigenomic studies, with emphasis on single cell analysis. We envision rapid growth in these directions, driven by the needs for testing scarce primary cell samples from patients in the context of precision medicine. PMID:28396707

Integrated Analysis of the Transcriptome and Metabolome of Corynebacterium glutamicum during Penicillin-Induced Glutamic Acid Production.

PubMed

Hirasawa, Takashi; Saito, Masaki; Yoshikawa, Katsunori; Furusawa, Chikara; Shmizu, Hiroshi

2018-05-01

Corynebacterium glutamicum is known for its ability to produce glutamic acid and has been utilized for the fermentative production of various amino acids. Glutamic acid production in C. glutamicum is induced by penicillin. In this study, the transcriptome and metabolome of C. glutamicum is analyzed to understand the mechanism of penicillin-induced glutamic acid production. Transcriptomic analysis with DNA microarray revealed that expression of some glycolysis- and TCA cycle-related genes, which include those encoding the enzymes involved in conversion of glucose to 2-oxoglutaric acid, is upregulated after penicillin addition. Meanwhile, expression of some TCA cycle-related genes, encoding the enzymes for conversion of 2-oxoglutaric acid to oxaloacetic acid, and the anaplerotic reactions decreased. In addition, expression of NCgl1221 and odhI, encoding proteins involved in glutamic acid excretion and inhibition of the 2-oxoglutarate dehydrogenase, respectively, is upregulated. Functional category enrichment analysis of genes upregulated and downregulated after penicillin addition revealed that genes for signal transduction systems are enriched among upregulated genes, whereas those for energy production and carbohydrate and amino acid metabolisms are enriched among the downregulated genes. As for the metabolomic analysis using capillary electrophoresis time-of-flight mass spectrometry, the intracellular content of most metabolites of the glycolysis and the TCA cycle decreased dramatically after penicillin addition. Overall, these results indicate that the cellular metabolism and glutamic acid excretion are mainly optimized at the transcription level during penicillin-induced glutamic acid production by C. glutamicum. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Growth in spaceflight hardware results in alterations to the transcriptome and proteome.

PubMed

Basu, Proma; Kruse, Colin P S; Luesse, Darron R; Wyatt, Sarah E

2017-11-01

The Biological Research in Canisters (BRIC) hardware has been used to house many biology experiments on both the Space Transport System (STS, commonly known as the space shuttle) and the International Space Station (ISS). However, microscopic examination of Arabidopsis seedlings by Johnson et al. (2015) indicated the hardware itself may affect cell morphology. The experiment herein was designed to assess the effects of the BRIC-Petri Dish Fixation Units (BRIC-PDFU) hardware on the transcriptome and proteome of Arabidopsis seedlings. To our knowledge, this is the first transcriptomic and proteomic comparison of Arabidopsis seedlings grown with and without hardware. Arabidopsis thaliana wild-type Columbia (Col-0) seeds were sterilized and bulk plated on forty-four 60 mm Petri plates, of which 22 were integrated into the BRIC-PDFU hardware and 22 were maintained in closed containers at Ohio University. Seedlings were grown for approximately 3 days, fixed with RNAlater ® and stored at -80 °C prior to RNA and protein extraction, with proteins separated into membrane and soluble fractions prior to analysis. The RNAseq analysis identified 1651 differentially expressed genes; MS/MS analysis identified 598 soluble and 589 membrane proteins differentially abundant both at p < .05. Fold enrichment analysis of gene ontology terms related to differentially expressed transcripts and proteins highlighted a variety of stress responses. Some of these genes and proteins have been previously identified in spaceflight experiments, indicating that these genes and proteins may be perturbed by both conditions. Copyright © 2017 The Committee on Space Research (COSPAR). Published by Elsevier Ltd. All rights reserved.

PEA: an integrated R toolkit for plant epitranscriptome analysis.

PubMed

Zhai, Jingjing; Song, Jie; Cheng, Qian; Tang, Yunjia; Ma, Chuang

2018-05-29

The epitranscriptome, also known as chemical modifications of RNA (CMRs), is a newly discovered layer of gene regulation, the biological importance of which emerged through analysis of only a small fraction of CMRs detected by high-throughput sequencing technologies. Understanding of the epitranscriptome is hampered by the absence of computational tools for the systematic analysis of epitranscriptome sequencing data. In addition, no tools have yet been designed for accurate prediction of CMRs in plants, or to extend epitranscriptome analysis from a fraction of the transcriptome to its entirety. Here, we introduce PEA, an integrated R toolkit to facilitate the analysis of plant epitranscriptome data. The PEA toolkit contains a comprehensive collection of functions required for read mapping, CMR calling, motif scanning and discovery, and gene functional enrichment analysis. PEA also takes advantage of machine learning technologies for transcriptome-scale CMR prediction, with high prediction accuracy, using the Positive Samples Only Learning algorithm, which addresses the two-class classification problem by using only positive samples (CMRs), in the absence of negative samples (non-CMRs). Hence PEA is a versatile epitranscriptome analysis pipeline covering CMR calling, prediction, and annotation, and we describe its application to predict N6-methyladenosine (m6A) modifications in Arabidopsis thaliana. Experimental results demonstrate that the toolkit achieved 71.6% sensitivity and 73.7% specificity, which is superior to existing m6A predictors. PEA is potentially broadly applicable to the in-depth study of epitranscriptomics. PEA Docker image is available at https://hub.docker.com/r/malab/pea, source codes and user manual are available at https://github.com/cma2015/PEA. chuangma2006@gmail.com. Supplementary data are available at Bioinformatics online.

NGS-based approach to determine the presence of HPV and their sites of integration in human cancer genome.

PubMed

Chandrani, P; Kulkarni, V; Iyer, P; Upadhyay, P; Chaubal, R; Das, P; Mulherkar, R; Singh, R; Dutt, A

2015-06-09

Human papilloma virus (HPV) accounts for the most common cause of all virus-associated human cancers. Here, we describe the first graphic user interface (GUI)-based automated tool 'HPVDetector', for non-computational biologists, exclusively for detection and annotation of the HPV genome based on next-generation sequencing data sets. We developed a custom-made reference genome that comprises of human chromosomes along with annotated genome of 143 HPV types as pseudochromosomes. The tool runs on a dual mode as defined by the user: a 'quick mode' to identify presence of HPV types and an 'integration mode' to determine genomic location for the site of integration. The input data can be a paired-end whole-exome, whole-genome or whole-transcriptome data set. The HPVDetector is available in public domain for download: http://www.actrec.gov.in/pi-webpages/AmitDutt/HPVdetector/HPVDetector.html. On the basis of our evaluation of 116 whole-exome, 23 whole-transcriptome and 2 whole-genome data, we were able to identify presence of HPV in 20 exomes and 4 transcriptomes of cervical and head and neck cancer tumour samples. Using the inbuilt annotation module of HPVDetector, we found predominant integration of viral gene E7, a known oncogene, at known 17q21, 3q27, 7q35, Xq28 and novel sites of integration in the human genome. Furthermore, co-infection with high-risk HPVs such as 16 and 31 were found to be mutually exclusive compared with low-risk HPV71. HPVDetector is a simple yet precise and robust tool for detecting HPV from tumour samples using variety of next-generation sequencing platforms including whole genome, whole exome and transcriptome. Two different modes (quick detection and integration mode) along with a GUI widen the usability of HPVDetector for biologists and clinicians with minimal computational knowledge.

Dissection of Symbiosis and Organ Development by Integrated Transcriptome Analysis of Lotus japonicus Mutant and Wild-Type Plants

PubMed Central

Høgslund, Niels; Radutoiu, Simona; Krusell, Lene; Voroshilova, Vera; Hannah, Matthew A.; Goffard, Nicolas; Sanchez, Diego H.; Lippold, Felix; Ott, Thomas; Sato, Shusei; Tabata, Satoshi; Liboriussen, Poul; Lohmann, Gitte V.; Schauser, Leif; Weiller, Georg F.; Udvardi, Michael K.; Stougaard, Jens

2009-01-01

Genetic analyses of plant symbiotic mutants has led to the identification of key genes involved in Rhizobium-legume communication as well as in development and function of nitrogen fixing root nodules. However, the impact of these genes in coordinating the transcriptional programs of nodule development has only been studied in limited and isolated studies. Here, we present an integrated genome-wide analysis of transcriptome landscapes in Lotus japonicus wild-type and symbiotic mutant plants. Encompassing five different organs, five stages of the sequentially developed determinate Lotus root nodules, and eight mutants impaired at different stages of the symbiotic interaction, our data set integrates an unprecedented combination of organ- or tissue-specific profiles with mutant transcript profiles. In total, 38 different conditions sampled under the same well-defined growth regimes were included. This comprehensive analysis unravelled new and unexpected patterns of transcriptional regulation during symbiosis and organ development. Contrary to expectations, none of the previously characterized nodulins were among the 37 genes specifically expressed in nodules. Another surprise was the extensive transcriptional response in whole root compared to the susceptible root zone where the cellular response is most pronounced. A large number of transcripts predicted to encode transcriptional regulators, receptors and proteins involved in signal transduction, as well as many genes with unknown function, were found to be regulated during nodule organogenesis and rhizobial infection. Combining wild type and mutant profiles of these transcripts demonstrates the activation of a complex genetic program that delineates symbiotic nitrogen fixation. The complete data set was organized into an indexed expression directory that is accessible from a resource database, and here we present selected examples of biological questions that can be addressed with this comprehensive and powerful gene expression data set. PMID:19662091

A Comprehensive Transcriptomic and Proteomic Analysis of Hydra Head Regeneration

PubMed Central

Petersen, Hendrik O.; Höger, Stefanie K.; Looso, Mario; Lengfeld, Tobias; Kuhn, Anne; Warnken, Uwe; Nishimiya-Fujisawa, Chiemi; Schnölzer, Martina; Krüger, Marcus; Özbek, Suat; Simakov, Oleg; Holstein, Thomas W.

2015-01-01

The cnidarian freshwater polyp Hydra sp. exhibits an unparalleled regeneration capacity in the animal kingdom. Using an integrative transcriptomic and stable isotope labeling by amino acids in cell culture proteomic/phosphoproteomic approach, we studied stem cell-based regeneration in Hydra polyps. As major contributors to head regeneration, we identified diverse signaling pathways adopted for the regeneration response as well as enriched novel genes. Our global analysis reveals two distinct molecular cascades: an early injury response and a subsequent, signaling driven patterning of the regenerating tissue. A key factor of the initial injury response is a general stabilization of proteins and a net upregulation of transcripts, which is followed by a subsequent activation cascade of signaling molecules including Wnts and transforming growth factor (TGF) beta-related factors. We observed moderate overlap between the factors contributing to proteomic and transcriptomic responses suggesting a decoupled regulation between the transcriptional and translational levels. Our data also indicate that interstitial stem cells and their derivatives (e.g., neurons) have no major role in Hydra head regeneration. Remarkably, we found an enrichment of evolutionarily more recent genes in the early regeneration response, whereas conserved genes are more enriched in the late phase. In addition, genes specific to the early injury response were enriched in transposon insertions. Genetic dynamicity and taxon-specific factors might therefore play a hitherto underestimated role in Hydra regeneration. PMID:25841488

Regulatory complexity revealed by integrated cytological and RNA-seq analyses of meiotic substages in mouse spermatocytes.

PubMed

Ball, Robyn L; Fujiwara, Yasuhiro; Sun, Fengyun; Hu, Jianjun; Hibbs, Matthew A; Handel, Mary Ann; Carter, Gregory W

2016-08-12

The continuous and non-synchronous nature of postnatal male germ-cell development has impeded stage-specific resolution of molecular events of mammalian meiotic prophase in the testis. Here the juvenile onset of spermatogenesis in mice is analyzed by combining cytological and transcriptomic data in a novel computational analysis that allows decomposition of the transcriptional programs of spermatogonia and meiotic prophase substages. Germ cells from testes of individual mice were obtained at two-day intervals from 8 to 18 days post-partum (dpp), prepared as surface-spread chromatin and immunolabeled for meiotic stage-specific protein markers (STRA8, SYCP3, phosphorylated H2AFX, and HISTH1T). Eight stages were discriminated cytologically by combinatorial antibody labeling, and RNA-seq was performed on the same samples. Independent principal component analyses of cytological and transcriptomic data yielded similar patterns for both data types, providing strong evidence for substage-specific gene expression signatures. A novel permutation-based maximum covariance analysis (PMCA) was developed to map co-expressed transcripts to one or more of the eight meiotic prophase substages, thereby linking distinct molecular programs to cytologically defined cell states. Expression of meiosis-specific genes is not substage-limited, suggesting regulation of substage transitions at other levels. This integrated analysis provides a general method for resolving complex cell populations. Here it revealed not only features of meiotic substage-specific gene expression, but also a network of substage-specific transcription factors and relationships to potential target genes.

Identification of hypertension-related genes through an integrated genomic-transcriptomic approach.

PubMed

Yagil, Chana; Hubner, Norbert; Monti, Jan; Schulz, Herbert; Sapojnikov, Marina; Luft, Friedrich C; Ganten, Detlev; Yagil, Yoram

2005-04-01

In search for the genetic basis of hypertension, we applied an integrated genomic-transcriptomic approach to identify genes involved in the pathogenesis of hypertension in the Sabra rat model of salt-susceptibility. In the genomic arm of the project, we previously detected in male rats two salt-susceptibility QTLs on chromosome 1, SS1a (D1Mgh2-D1Mit11; span 43.1 cM) and SS1b (D1Mit11-D1Mit4; span 18 cM). In the transcriptomic arm, we studied differential gene expression in kidneys of SBH/y and SBN/y rats that had been fed regular diet or salt-loaded. We used the Affymetrix Rat Genome RAE230 GeneChip and probed >30,000 transcripts. The research algorithm called for an initial genome-wide screen for differentially expressed transcripts between the study groups. This step was followed by cluster analysis based on 2x2 ANOVA to identify transcripts that were of relevance specifically to salt-sensitivity and hypertension and to salt-resistance. The two arms of the project were integrated by identifying those differentially expressed transcripts that showed an allele-specific hypertensive effect on salt-loading and that mapped within the defined boundaries of the salt-susceptibility QTLs on chromosome 1. The differentially expressed transcripts were confirmed by RT-PCR. Of the 2933 genes annotated to rat chromosome 1, 1102 genes were identified within the boundaries of the two blood pressure QTLs. The microarray identified 2470 transcripts that were differentially expressed between the study groups. Cluster analysis identified genome-wide 192 genes that were relevant to salt-susceptibility and/or hypertension, 19 of which mapped to chromosome 1. Eight of these genes mapped within the boundaries of QTLs SS1a and SS1b. RT-PCR confirmed 7 genes, leaving TcTex1, Myadm, Lisch7, Axl-like, Fah, PRC1-like, and Serpinh1. None of these genes has been implicated in hypertension before. These genes become henceforth targets for our continuing search for the genetic basis of hypertension.

Topological analysis of metabolic networks integrating co-segregating transcriptomes and metabolomes in type 2 diabetic rat congenic series.

PubMed

Dumas, Marc-Emmanuel; Domange, Céline; Calderari, Sophie; Martínez, Andrea Rodríguez; Ayala, Rafael; Wilder, Steven P; Suárez-Zamorano, Nicolas; Collins, Stephan C; Wallis, Robert H; Gu, Quan; Wang, Yulan; Hue, Christophe; Otto, Georg W; Argoud, Karène; Navratil, Vincent; Mitchell, Steve C; Lindon, John C; Holmes, Elaine; Cazier, Jean-Baptiste; Nicholson, Jeremy K; Gauguier, Dominique

2016-09-30

The genetic regulation of metabolic phenotypes (i.e., metabotypes) in type 2 diabetes mellitus occurs through complex organ-specific cellular mechanisms and networks contributing to impaired insulin secretion and insulin resistance. Genome-wide gene expression profiling systems can dissect the genetic contributions to metabolome and transcriptome regulations. The integrative analysis of multiple gene expression traits and metabolic phenotypes (i.e., metabotypes) together with their underlying genetic regulation remains a challenge. Here, we introduce a systems genetics approach based on the topological analysis of a combined molecular network made of genes and metabolites identified through expression and metabotype quantitative trait locus mapping (i.e., eQTL and mQTL) to prioritise biological characterisation of candidate genes and traits. We used systematic metabotyping by 1 H NMR spectroscopy and genome-wide gene expression in white adipose tissue to map molecular phenotypes to genomic blocks associated with obesity and insulin secretion in a series of rat congenic strains derived from spontaneously diabetic Goto-Kakizaki (GK) and normoglycemic Brown-Norway (BN) rats. We implemented a network biology strategy approach to visualize the shortest paths between metabolites and genes significantly associated with each genomic block. Despite strong genomic similarities (95-99 %) among congenics, each strain exhibited specific patterns of gene expression and metabotypes, reflecting the metabolic consequences of series of linked genetic polymorphisms in the congenic intervals. We subsequently used the congenic panel to map quantitative trait loci underlying specific mQTLs and genome-wide eQTLs. Variation in key metabolites like glucose, succinate, lactate, or 3-hydroxybutyrate and second messenger precursors like inositol was associated with several independent genomic intervals, indicating functional redundancy in these regions. To navigate through the complexity of these association networks we mapped candidate genes and metabolites onto metabolic pathways and implemented a shortest path strategy to highlight potential mechanistic links between metabolites and transcripts at colocalized mQTLs and eQTLs. Minimizing the shortest path length drove prioritization of biological validations by gene silencing. These results underline the importance of network-based integration of multilevel systems genetics datasets to improve understanding of the genetic architecture of metabotype and transcriptomic regulation and to characterize novel functional roles for genes determining tissue-specific metabolism.

Understanding the response to endurance exercise using a systems biology approach: combining blood metabolomics, transcriptomics and miRNomics in horses.

PubMed

Mach, Núria; Ramayo-Caldas, Yuliaxis; Clark, Allison; Moroldo, Marco; Robert, Céline; Barrey, Eric; López, Jesús Maria; Le Moyec, Laurence

2017-02-17

Endurance exercise in horses requires adaptive processes involving physiological, biochemical, and cognitive-behavioral responses in an attempt to regain homeostasis. We hypothesized that the identification of the relationships between blood metabolome, transcriptome, and miRNome during endurance exercise in horses could provide significant insights into the molecular response to endurance exercise. For this reason, the serum metabolome and whole-blood transcriptome and miRNome data were obtained from ten horses before and after a 160 km endurance competition. We obtained a global regulatory network based on 11 unique metabolites, 263 metabolic genes and 5 miRNAs whose expression was significantly altered at T1 (post- endurance competition) relative to T0 (baseline, pre-endurance competition). This network provided new insights into the cross talk between the distinct molecular pathways (e.g. energy and oxygen sensing, oxidative stress, and inflammation) that were not detectable when analyzing single metabolites or transcripts alone. Single metabolites and transcripts were carrying out multiple roles and thus sharing several biochemical pathways. Using a regulatory impact factor metric analysis, this regulatory network was further confirmed at the transcription factor and miRNA levels. In an extended cohort of 31 independent animals, multiple factor analysis confirmed the strong associations between lactate, methylene derivatives, miR-21-5p, miR-16-5p, let-7 family and genes that coded proteins involved in metabolic reactions primarily related to energy, ubiquitin proteasome and lipopolysaccharide immune responses after the endurance competition. Multiple factor analysis also identified potential biomarkers at T0 for an increased likelihood for failure to finish an endurance competition. To the best of our knowledge, the present study is the first to provide a comprehensive and integrated overview of the metabolome, transcriptome, and miRNome co-regulatory networks that may have a key role in regulating the metabolic and immune response to endurance exercise in horses.

Integrative Transcriptome Profiling of Cognitive Aging and Its Preservation through Ser/Thr Protein Phosphatase Regulation.

PubMed

Park, C Sehwan; Valomon, Amandine; Welzl, Hans

2015-01-01

Environmental enrichment has been reported to delay or restore age-related cognitive deficits, however, a mechanism to account for the cause and progression of normal cognitive decline and its preservation by environmental enrichment is lacking. Using genome-wide SAGE-Seq, we provide a global assessment of differentially expressed genes altered with age and environmental enrichment in the hippocampus. Qualitative and quantitative proteomics in naïve young and aged mice was used to further identify phosphorylated proteins differentially expressed with age. We found that increased expression of endogenous protein phosphatase-1 inhibitors in aged mice may be characteristic of long-term environmental enrichment and improved cognitive status. As such, hippocampus-dependent performances in spatial, recognition, and associative memories, which are sensitive to aging, were preserved by environmental enrichment and accompanied by decreased protein phosphatase activity. Age-associated phosphorylated proteins were also found to correspond to the functional categories of age-associated genes identified through transcriptome analysis. Together, this study provides a comprehensive map of the transcriptome and proteome in the aging brain, and elucidates endogenous protein phosphatase-1 inhibition as a potential means through which environmental enrichment may ameliorate age-related cognitive deficits.

Comparative Transcriptomics Among Four White Pine Species

PubMed Central

Baker, Ethan A. G.; Wegrzyn, Jill L.; Sezen, Uzay U.; Falk, Taylor; Maloney, Patricia E.; Vogler, Detlev R.; Delfino-Mix, Annette; Jensen, Camille; Mitton, Jeffry; Wright, Jessica; Knaus, Brian; Rai, Hardeep; Cronn, Richard; Gonzalez-Ibeas, Daniel; Vasquez-Gross, Hans A.; Famula, Randi A.; Liu, Jun-Jun; Kueppers, Lara M.; Neale, David B.

2018-01-01

Conifers are the dominant plant species throughout the high latitude boreal forests as well as some lower latitude temperate forests of North America, Europe, and Asia. As such, they play an integral economic and ecological role across much of the world. This study focused on the characterization of needle transcriptomes from four ecologically important and understudied North American white pines within the Pinus subgenus Strobus. The populations of many Strobus species are challenged by native and introduced pathogens, native insects, and abiotic factors. RNA from the needles of western white pine (Pinus monticola), limber pine (Pinus flexilis), whitebark pine (Pinus albicaulis), and sugar pine (Pinus lambertiana) was sampled, Illumina short read sequenced, and de novo assembled. The assembled transcripts and their subsequent structural and functional annotations were processed through custom pipelines to contend with the challenges of non-model organism transcriptome validation. Orthologous gene family analysis of over 58,000 translated transcripts, implemented through Tribe-MCL, estimated the shared and unique gene space among the four species. This revealed 2025 conserved gene families, of which 408 were aligned to estimate levels of divergence and reveal patterns of selection. Specific candidate genes previously associated with drought tolerance and white pine blister rust resistance in conifers were investigated. PMID:29559535

Virus-Clip: a fast and memory-efficient viral integration site detection tool at single-base resolution with annotation capability.

PubMed

Ho, Daniel W H; Sze, Karen M F; Ng, Irene O L

2015-08-28

Viral integration into the human genome upon infection is an important risk factor for various human malignancies. We developed viral integration site detection tool called Virus-Clip, which makes use of information extracted from soft-clipped sequencing reads to identify exact positions of human and virus breakpoints of integration events. With initial read alignment to virus reference genome and streamlined procedures, Virus-Clip delivers a simple, fast and memory-efficient solution to viral integration site detection. Moreover, it can also automatically annotate the integration events with the corresponding affected human genes. Virus-Clip has been verified using whole-transcriptome sequencing data and its detection was validated to have satisfactory sensitivity and specificity. Marked advancement in performance was detected, compared to existing tools. It is applicable to versatile types of data including whole-genome sequencing, whole-transcriptome sequencing, and targeted sequencing. Virus-Clip is available at http://web.hku.hk/~dwhho/Virus-Clip.zip.

Integrative Analysis of Longitudinal Metabolomics Data from a Personal Multi-Omics Profile

PubMed Central

Stanberry, Larissa; Mias, George I.; Haynes, Winston; Higdon, Roger; Snyder, Michael; Kolker, Eugene

2013-01-01

The integrative personal omics profile (iPOP) is a pioneering study that combines genomics, transcriptomics, proteomics, metabolomics and autoantibody profiles from a single individual over a 14-month period. The observation period includes two episodes of viral infection: a human rhinovirus and a respiratory syncytial virus. The profile studies give an informative snapshot into the biological functioning of an organism. We hypothesize that pathway expression levels are associated with disease status. To test this hypothesis, we use biological pathways to integrate metabolomics and proteomics iPOP data. The approach computes the pathways’ differential expression levels at each time point, while taking into account the pathway structure and the longitudinal design. The resulting pathway levels show strong association with the disease status. Further, we identify temporal patterns in metabolite expression levels. The changes in metabolite expression levels also appear to be consistent with the disease status. The results of the integrative analysis suggest that changes in biological pathways may be used to predict and monitor the disease. The iPOP experimental design, data acquisition and analysis issues are discussed within the broader context of personal profiling. PMID:24958148

Preliminary profiling of blood transcriptome in a rat model of hemorrhagic shock

PubMed Central

Braga, D; Barcella, M; D’Avila, F; Lupoli, S; Tagliaferri, F; Santamaria, MH; DeLano, FA; Baselli, G; Schmid-Schönbein, GW; Kistler, EB; Aletti, F

2017-01-01

Hemorrhagic shock is a leading cause of morbidity and mortality worldwide. Significant blood loss may lead to decreased blood pressure and inadequate tissue perfusion with resultant organ failure and death, even after replacement of lost blood volume. One reason for this high acuity is that the fundamental mechanisms of shock are poorly understood. Proteomic and metabolomic approaches have been used to investigate the molecular events occurring in hemorrhagic shock but, to our knowledge, a systematic analysis of the transcriptomic profile is missing. Therefore, a pilot analysis using paired-end RNA sequencing was used to identify changes that occur in the blood transcriptome of rats subjected to hemorrhagic shock after blood reinfusion. Hemorrhagic shock was induced using a Wigger’s shock model. The transcriptome of whole blood from shocked animals shows modulation of genes related to inflammation and immune response (Tlr13, Il1b, Ccl6, Lgals3), antioxidant functions (Mt2A, Mt1), tissue injury and repair pathways (Gpnmb, Trim72) and lipid mediators (Alox5ap, Ltb4r, Ptger2) compared with control animals. These findings are congruent with results obtained in hemorrhagic shock analysis by other authors using metabolomics and proteomics. The analysis of blood transcriptome may be a valuable tool to understand the biological changes occurring in hemorrhagic shock and a promising approach for the identification of novel biomarkers and therapeutic targets. Impact statement This study provides the first pilot analysis of the changes occurring in transcriptome expression of whole blood in hemorrhagic shock (HS) rats. We showed that the analysis of blood transcriptome is a useful approach to investigate pathways and functional alterations in this disease condition. This pilot study encourages the possible application of transcriptome analysis in the clinical setting, for the molecular profiling of whole blood in HS patients. PMID:28661205

N-of-1-pathways MixEnrich: advancing precision medicine via single-subject analysis in discovering dynamic changes of transcriptomes.

PubMed

Li, Qike; Schissler, A Grant; Gardeux, Vincent; Achour, Ikbel; Kenost, Colleen; Berghout, Joanne; Li, Haiquan; Zhang, Hao Helen; Lussier, Yves A

2017-05-24

Transcriptome analytic tools are commonly used across patient cohorts to develop drugs and predict clinical outcomes. However, as precision medicine pursues more accurate and individualized treatment decisions, these methods are not designed to address single-patient transcriptome analyses. We previously developed and validated the N-of-1-pathways framework using two methods, Wilcoxon and Mahalanobis Distance (MD), for personal transcriptome analysis derived from a pair of samples of a single patient. Although, both methods uncover concordantly dysregulated pathways, they are not designed to detect dysregulated pathways with up- and down-regulated genes (bidirectional dysregulation) that are ubiquitous in biological systems. We developed N-of-1-pathways MixEnrich, a mixture model followed by a gene set enrichment test, to uncover bidirectional and concordantly dysregulated pathways one patient at a time. We assess its accuracy in a comprehensive simulation study and in a RNA-Seq data analysis of head and neck squamous cell carcinomas (HNSCCs). In presence of bidirectionally dysregulated genes in the pathway or in presence of high background noise, MixEnrich substantially outperforms previous single-subject transcriptome analysis methods, both in the simulation study and the HNSCCs data analysis (ROC Curves; higher true positive rates; lower false positive rates). Bidirectional and concordant dysregulated pathways uncovered by MixEnrich in each patient largely overlapped with the quasi-gold standard compared to other single-subject and cohort-based transcriptome analyses. The greater performance of MixEnrich presents an advantage over previous methods to meet the promise of providing accurate personal transcriptome analysis to support precision medicine at point of care.

Integrated Genomics Reveals Convergent Transcriptomic Networks Underlying Chronic Obstructive Pulmonary Disease and Idiopathic Pulmonary Fibrosis.

PubMed

Kusko, Rebecca L; Brothers, John F; Tedrow, John; Pandit, Kusum; Huleihel, Luai; Perdomo, Catalina; Liu, Gang; Juan-Guardela, Brenda; Kass, Daniel; Zhang, Sherry; Lenburg, Marc; Martinez, Fernando; Quackenbush, John; Sciurba, Frank; Limper, Andrew; Geraci, Mark; Yang, Ivana; Schwartz, David A; Beane, Jennifer; Spira, Avrum; Kaminski, Naftali

2016-10-15

Despite shared environmental exposures, idiopathic pulmonary fibrosis (IPF) and chronic obstructive pulmonary disease are usually studied in isolation, and the presence of shared molecular mechanisms is unknown. We applied an integrative genomic approach to identify convergent transcriptomic pathways in emphysema and IPF. We defined the transcriptional repertoire of chronic obstructive pulmonary disease, IPF, or normal histology lungs using RNA-seq (n = 87). Genes increased in both emphysema and IPF relative to control were enriched for the p53/hypoxia pathway, a finding confirmed in an independent cohort using both gene expression arrays and the nCounter Analysis System (n = 193). Immunohistochemistry confirmed overexpression of HIF1A, MDM2, and NFKBIB members of this pathway in tissues from patients with emphysema or IPF. Using reads aligned across splice junctions, we determined that alternative splicing of p53/hypoxia pathway-associated molecules NUMB and PDGFA occurred more frequently in IPF or emphysema compared with control and validated these findings by quantitative polymerase chain reaction and the nCounter Analysis System on an independent sample set (n = 193). Finally, by integrating parallel microRNA and mRNA-Seq data on the same samples, we identified MIR96 as a key novel regulatory hub in the p53/hypoxia gene-expression network and confirmed that modulation of MIR96 in vitro recapitulates the disease-associated gene-expression network. Our results suggest convergent transcriptional regulatory hubs in diseases as varied phenotypically as chronic obstructive pulmonary disease and IPF and suggest that these hubs may represent shared key responses of the lung to environmental stresses.

The Transcriptome Analysis and Comparison Explorer--T-ACE: a platform-independent, graphical tool to process large RNAseq datasets of non-model organisms.

PubMed

Philipp, E E R; Kraemer, L; Mountfort, D; Schilhabel, M; Schreiber, S; Rosenstiel, P

2012-03-15

Next generation sequencing (NGS) technologies allow a rapid and cost-effective compilation of large RNA sequence datasets in model and non-model organisms. However, the storage and analysis of transcriptome information from different NGS platforms is still a significant bottleneck, leading to a delay in data dissemination and subsequent biological understanding. Especially database interfaces with transcriptome analysis modules going beyond mere read counts are missing. Here, we present the Transcriptome Analysis and Comparison Explorer (T-ACE), a tool designed for the organization and analysis of large sequence datasets, and especially suited for transcriptome projects of non-model organisms with little or no a priori sequence information. T-ACE offers a TCL-based interface, which accesses a PostgreSQL database via a php-script. Within T-ACE, information belonging to single sequences or contigs, such as annotation or read coverage, is linked to the respective sequence and immediately accessible. Sequences and assigned information can be searched via keyword- or BLAST-search. Additionally, T-ACE provides within and between transcriptome analysis modules on the level of expression, GO terms, KEGG pathways and protein domains. Results are visualized and can be easily exported for external analysis. We developed T-ACE for laboratory environments, which have only a limited amount of bioinformatics support, and for collaborative projects in which different partners work on the same dataset from different locations or platforms (Windows/Linux/MacOS). For laboratories with some experience in bioinformatics and programming, the low complexity of the database structure and open-source code provides a framework that can be customized according to the different needs of the user and transcriptome project.

Predicting gene regulatory networks of soybean nodulation from RNA-Seq transcriptome data.

PubMed

Zhu, Mingzhu; Dahmen, Jeremy L; Stacey, Gary; Cheng, Jianlin

2013-09-22

High-throughput RNA sequencing (RNA-Seq) is a revolutionary technique to study the transcriptome of a cell under various conditions at a systems level. Despite the wide application of RNA-Seq techniques to generate experimental data in the last few years, few computational methods are available to analyze this huge amount of transcription data. The computational methods for constructing gene regulatory networks from RNA-Seq expression data of hundreds or even thousands of genes are particularly lacking and urgently needed. We developed an automated bioinformatics method to predict gene regulatory networks from the quantitative expression values of differentially expressed genes based on RNA-Seq transcriptome data of a cell in different stages and conditions, integrating transcriptional, genomic and gene function data. We applied the method to the RNA-Seq transcriptome data generated for soybean root hair cells in three different development stages of nodulation after rhizobium infection. The method predicted a soybean nodulation-related gene regulatory network consisting of 10 regulatory modules common for all three stages, and 24, 49 and 70 modules separately for the first, second and third stage, each containing both a group of co-expressed genes and several transcription factors collaboratively controlling their expression under different conditions. 8 of 10 common regulatory modules were validated by at least two kinds of validations, such as independent DNA binding motif analysis, gene function enrichment test, and previous experimental data in the literature. We developed a computational method to reliably reconstruct gene regulatory networks from RNA-Seq transcriptome data. The method can generate valuable hypotheses for interpreting biological data and designing biological experiments such as ChIP-Seq, RNA interference, and yeast two hybrid experiments.

Global transcriptomic profiling using small volumes of whole blood: a cost-effective method for translational genomic biomarker identification in small animals.

PubMed

Fricano, Meagan M; Ditewig, Amy C; Jung, Paul M; Liguori, Michael J; Blomme, Eric A G; Yang, Yi

2011-01-01

Blood is an ideal tissue for the identification of novel genomic biomarkers for toxicity or efficacy. However, using blood for transcriptomic profiling presents significant technical challenges due to the transcriptomic changes induced by ex vivo handling and the interference of highly abundant globin mRNA. Most whole blood RNA stabilization and isolation methods also require significant volumes of blood, limiting their effective use in small animal species, such as rodents. To overcome these challenges, a QIAzol-based RNA stabilization and isolation method (QSI) was developed to isolate sufficient amounts of high quality total RNA from 25 to 500 μL of rat whole blood. The method was compared to the standard PAXgene Blood RNA System using blood collected from rats exposed to saline or lipopolysaccharide (LPS). The QSI method yielded an average of 54 ng total RNA per μL of rat whole blood with an average RNA Integrity Number (RIN) of 9, a performance comparable with the standard PAXgene method. Total RNA samples were further processed using the NuGEN Ovation Whole Blood Solution system and cDNA was hybridized to Affymetrix Rat Genome 230 2.0 Arrays. The microarray QC parameters using RNA isolated with the QSI method were within the acceptable range for microarray analysis. The transcriptomic profiles were highly correlated with those using RNA isolated with the PAXgene method and were consistent with expected LPS-induced inflammatory responses. The present study demonstrated that the QSI method coupled with NuGEN Ovation Whole Blood Solution system is cost-effective and particularly suitable for transcriptomic profiling of minimal volumes of whole blood, typical of those obtained with small animal species.

Transcriptome Assembly and Analysis of Tibetan Hulless Barley (Hordeum vulgare L. var. nudum) Developing Grains, with Emphasis on Quality Properties

PubMed Central

Chen, Xin; Long, Hai; Gao, Ping; Deng, Guangbing; Pan, Zhifen; Liang, Junjun; Tang, Yawei; Tashi, Nyima; Yu, Maoqun

2014-01-01

Background Hulless barley is attracting increasing attention due to its unique nutritional value and potential health benefits. However, the molecular biology of the barley grain development and nutrient storage are not well understood. Furthermore, the genetic potential of hulless barley has not been fully tapped for breeding. Methodology/Principal Findings In the present study, we investigated the transcriptome features during hulless barley grain development. Using Illumina paired-end RNA-Sequencing, we generated two data sets of the developing grain transcriptomes from two hulless barley landraces. A total of 13.1 and 12.9 million paired-end reads with lengths of 90 bp were generated from the two varieties and were assembled to 48,863 and 45,788 unigenes, respectively. A combined dataset of 46,485 All-Unigenes were generated from two transcriptomes with an average length of 542 bp, and 36,278 among were annotated with gene descriptions, conserved protein domains or gene ontology terms. Furthermore, sequences and expression levels of genes related to the biosynthesis of storage reserve compounds (starch, protein, and β-glucan) were analyzed, and their temporal and spatial patterns were deduced from the transcriptome data of cultivated barley Morex. Conclusions/Significance We established a sequences and functional annotation integrated database and examined the expression profiles of the developing grains of Tibetan hulless barley. The characterization of genes encoding storage proteins and enzymes of starch synthesis and (1–3;1–4)-β-D-glucan synthesis provided an overview of changes in gene expression associated with grain nutrition and health properties. Furthermore, the characterization of these genes provides a gene reservoir, which helps in quality improvement of hulless barley. PMID:24871534

An integrative analysis of tissue-specific transcriptomic and metabolomic responses to short-term dietary methionine restriction in mice

PubMed Central

Ghosh, Sujoy; Forney, Laura A.; Wanders, Desiree; Stone, Kirsten P.

2017-01-01

Dietary methionine restriction (MR) produces a coordinated series of transcriptional responses in peripheral tissues that limit fat accretion, remodel lipid metabolism in liver and adipose tissue, and improve overall insulin sensitivity. Hepatic sensing of reduced methionine leads to induction and release of fibroblast growth factor 21 (FGF21), which acts centrally to increase sympathetic tone and activate thermogenesis in adipose tissue. FGF21 also has direct effects in adipose to enhance glucose uptake and oxidation. However, an understanding of how the liver senses and translates reduced dietary methionine into these transcriptional programs remains elusive. A comprehensive systems biology approach integrating transcriptomic and metabolomic readouts in MR-treated mice confirmed that three interconnected mechanisms (fatty acid transport and oxidation, tricarboxylic acid cycle, and oxidative phosphorylation) were activated in MR-treated inguinal adipose tissue. In contrast, the effects of MR in liver involved up-regulation of anti-oxidant responses driven by the nuclear factor, erythroid 2 like 2 transcription factor, NFE2L2. Metabolomic analysis provided evidence for redox imbalance, stemming from large reductions in the master anti-oxidant molecule glutathione coupled with disproportionate increases in ophthalmate and its precursors, glutamate and 2-aminobutyrate. Thus, cysteine and its downstream product, glutathione, emerge as key early hepatic signaling molecules linking dietary MR to its metabolic phenotype. PMID:28520765

Tools to covisualize and coanalyze proteomic data with genomes and transcriptomes: validation of genes and alternative mRNA splicing.

PubMed

Pang, Chi Nam Ignatius; Tay, Aidan P; Aya, Carlos; Twine, Natalie A; Harkness, Linda; Hart-Smith, Gene; Chia, Samantha Z; Chen, Zhiliang; Deshpande, Nandan P; Kaakoush, Nadeem O; Mitchell, Hazel M; Kassem, Moustapha; Wilkins, Marc R

2014-01-03

Direct links between proteomic and genomic/transcriptomic data are not frequently made, partly because of lack of appropriate bioinformatics tools. To help address this, we have developed the PG Nexus pipeline. The PG Nexus allows users to covisualize peptides in the context of genomes or genomic contigs, along with RNA-seq reads. This is done in the Integrated Genome Viewer (IGV). A Results Analyzer reports the precise base position where LC-MS/MS-derived peptides cover genes or gene isoforms, on the chromosomes or contigs where this occurs. In prokaryotes, the PG Nexus pipeline facilitates the validation of genes, where annotation or gene prediction is available, or the discovery of genes using a "virtual protein"-based unbiased approach. We illustrate this with a comprehensive proteogenomics analysis of two strains of Campylobacter concisus . For higher eukaryotes, the PG Nexus facilitates gene validation and supports the identification of mRNA splice junction boundaries and splice variants that are protein-coding. This is illustrated with an analysis of splice junctions covered by human phosphopeptides, and other examples of relevance to the Chromosome-Centric Human Proteome Project. The PG Nexus is open-source and available from https://github.com/IntersectAustralia/ap11_Samifier. It has been integrated into Galaxy and made available in the Galaxy tool shed.

An integrated genomic and transcriptomic survey of mucormycosis-causing fungi

PubMed Central

Chibucos, Marcus C.; Soliman, Sameh; Gebremariam, Teclegiorgis; Lee, Hongkyu; Daugherty, Sean; Orvis, Joshua; Shetty, Amol C.; Crabtree, Jonathan; Hazen, Tracy H.; Etienne, Kizee A.; Kumari, Priti; O'Connor, Timothy D.; Rasko, David A.; Filler, Scott G.; Fraser, Claire M.; Lockhart, Shawn R.; Skory, Christopher D.; Ibrahim, Ashraf S.; Bruno, Vincent M.

2016-01-01

Mucormycosis is a life-threatening infection caused by Mucorales fungi. Here we sequence 30 fungal genomes, and perform transcriptomics with three representative Rhizopus and Mucor strains and with human airway epithelial cells during fungal invasion, to reveal key host and fungal determinants contributing to pathogenesis. Analysis of the host transcriptional response to Mucorales reveals platelet-derived growth factor receptor B (PDGFRB) signaling as part of a core response to divergent pathogenic fungi; inhibition of PDGFRB reduces Mucorales-induced damage to host cells. The unique presence of CotH invasins in all invasive Mucorales, and the correlation between CotH gene copy number and clinical prevalence, are consistent with an important role for these proteins in mucormycosis pathogenesis. Our work provides insight into the evolution of this medically and economically important group of fungi, and identifies several molecular pathways that might be exploited as potential therapeutic targets. PMID:27447865

Combined Large-Scale Phenotyping and Transcriptomics in Maize Reveals a Robust Growth Regulatory Network1[OPEN

PubMed Central

Herman, Dorota; Slabbinck, Bram; Pè, Mario Enrico

2016-01-01

Leaves are vital organs for biomass and seed production because of their role in the generation of metabolic energy and organic compounds. A better understanding of the molecular networks underlying leaf development is crucial to sustain global requirements for food and renewable energy. Here, we combined transcriptome profiling of proliferative leaf tissue with in-depth phenotyping of the fourth leaf at later stages of development in 197 recombinant inbred lines of two different maize (Zea mays) populations. Previously, correlation analysis in a classical biparental mapping population identified 1,740 genes correlated with at least one of 14 traits. Here, we extended these results with data from a multiparent advanced generation intercross population. As expected, the phenotypic variability was found to be larger in the latter population than in the biparental population, although general conclusions on the correlations among the traits are comparable. Data integration from the two diverse populations allowed us to identify a set of 226 genes that are robustly associated with diverse leaf traits. This set of genes is enriched for transcriptional regulators and genes involved in protein synthesis and cell wall metabolism. In order to investigate the molecular network context of the candidate gene set, we integrated our data with publicly available functional genomics data and identified a growth regulatory network of 185 genes. Our results illustrate the power of combining in-depth phenotyping with transcriptomics in mapping populations to dissect the genetic control of complex traits and present a set of candidate genes for use in biomass improvement. PMID:26754667

Genome-wide inference of regulatory networks in Streptomyces coelicolor.

PubMed

Castro-Melchor, Marlene; Charaniya, Salim; Karypis, George; Takano, Eriko; Hu, Wei-Shou

2010-10-18

The onset of antibiotics production in Streptomyces species is co-ordinated with differentiation events. An understanding of the genetic circuits that regulate these coupled biological phenomena is essential to discover and engineer the pharmacologically important natural products made by these species. The availability of genomic tools and access to a large warehouse of transcriptome data for the model organism, Streptomyces coelicolor, provides incentive to decipher the intricacies of the regulatory cascades and develop biologically meaningful hypotheses. In this study, more than 500 samples of genome-wide temporal transcriptome data, comprising wild-type and more than 25 regulatory gene mutants of Streptomyces coelicolor probed across multiple stress and medium conditions, were investigated. Information based on transcript and functional similarity was used to update a previously-predicted whole-genome operon map and further applied to predict transcriptional networks constituting modules enriched in diverse functions such as secondary metabolism, and sigma factor. The predicted network displays a scale-free architecture with a small-world property observed in many biological networks. The networks were further investigated to identify functionally-relevant modules that exhibit functional coherence and a consensus motif in the promoter elements indicative of DNA-binding elements. Despite the enormous experimental as well as computational challenges, a systems approach for integrating diverse genome-scale datasets to elucidate complex regulatory networks is beginning to emerge. We present an integrated analysis of transcriptome data and genomic features to refine a whole-genome operon map and to construct regulatory networks at the cistron level in Streptomyces coelicolor. The functionally-relevant modules identified in this study pose as potential targets for further studies and verification.

Integrating Transcriptome and Genome Re-Sequencing Data to Identify Key Genes and Mutations Affecting Chicken Eggshell Qualities

PubMed Central

Liu, Long; Zheng, Chuan Wei; Wang, De He; Hou, Zhuo Cheng; Ning, Zhong Hua

2015-01-01

Eggshell damages lead to economic losses in the egg production industry and are a threat to human health. We examined 49-wk-old Rhode Island White hens (Gallus gallus) that laid eggs having shells with significantly different strengths and thicknesses. We used HiSeq 2000 (Illumina) sequencing to characterize the chicken transcriptome and whole genome to identify the key genes and genetic mutations associated with eggshell calcification. We identified a total of 14,234 genes expressed in the chicken uterus, representing 89% of all annotated chicken genes. A total of 889 differentially expressed genes were identified by comparing low eggshell strength (LES) and normal eggshell strength (NES) genomes. The DEGs are enriched in calcification-related processes, including calcium ion transport and calcium signaling pathways as reveled by gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) pathway analysis. Some important matrix proteins, such as OC-116, LTF and SPP1, were also expressed differentially between two groups. A total of 3,671,919 single-nucleotide polymorphisms (SNPs) and 508,035 Indels were detected in protein coding genes by whole-genome re-sequencing, including 1775 non-synonymous variations and 19 frame-shift Indels in DEGs. SNPs and Indels found in this study could be further investigated for eggshell traits. This is the first report to integrate the transcriptome and genome re-sequencing to target the genetic variations which decreased the eggshell qualities. These findings further advance our understanding of eggshell calcification in the chicken uterus. PMID:25974068

Combined Large-Scale Phenotyping and Transcriptomics in Maize Reveals a Robust Growth Regulatory Network.

PubMed

Baute, Joke; Herman, Dorota; Coppens, Frederik; De Block, Jolien; Slabbinck, Bram; Dell'Acqua, Matteo; Pè, Mario Enrico; Maere, Steven; Nelissen, Hilde; Inzé, Dirk

2016-03-01

Leaves are vital organs for biomass and seed production because of their role in the generation of metabolic energy and organic compounds. A better understanding of the molecular networks underlying leaf development is crucial to sustain global requirements for food and renewable energy. Here, we combined transcriptome profiling of proliferative leaf tissue with in-depth phenotyping of the fourth leaf at later stages of development in 197 recombinant inbred lines of two different maize (Zea mays) populations. Previously, correlation analysis in a classical biparental mapping population identified 1,740 genes correlated with at least one of 14 traits. Here, we extended these results with data from a multiparent advanced generation intercross population. As expected, the phenotypic variability was found to be larger in the latter population than in the biparental population, although general conclusions on the correlations among the traits are comparable. Data integration from the two diverse populations allowed us to identify a set of 226 genes that are robustly associated with diverse leaf traits. This set of genes is enriched for transcriptional regulators and genes involved in protein synthesis and cell wall metabolism. In order to investigate the molecular network context of the candidate gene set, we integrated our data with publicly available functional genomics data and identified a growth regulatory network of 185 genes. Our results illustrate the power of combining in-depth phenotyping with transcriptomics in mapping populations to dissect the genetic control of complex traits and present a set of candidate genes for use in biomass improvement. © 2016 American Society of Plant Biologists. All Rights Reserved.

Snake venoms are integrated systems, but abundant venom proteins evolve more rapidly.

PubMed

Aird, Steven D; Aggarwal, Shikha; Villar-Briones, Alejandro; Tin, Mandy Man-Ying; Terada, Kouki; Mikheyev, Alexander S

2015-08-28

While many studies have shown that extracellular proteins evolve rapidly, how selection acts on them remains poorly understood. We used snake venoms to understand the interaction between ecology, expression level, and evolutionary rate in secreted protein systems. Venomous snakes employ well-integrated systems of proteins and organic constituents to immobilize prey. Venoms are generally optimized to subdue preferred prey more effectively than non-prey, and many venom protein families manifest positive selection and rapid gene family diversification. Although previous studies have illuminated how individual venom protein families evolve, how selection acts on venoms as integrated systems, is unknown. Using next-generation transcriptome sequencing and mass spectrometry, we examined microevolution in two pitvipers, allopatrically separated for at least 1.6 million years, and their hybrids. Transcriptomes of parental species had generally similar compositions in regard to protein families, but for a given protein family, the homologs present and concentrations thereof sometimes differed dramatically. For instance, a phospholipase A2 transcript comprising 73.4 % of the Protobothrops elegans transcriptome, was barely present in the P. flavoviridis transcriptome (<0.05 %). Hybrids produced most proteins found in both parental venoms. Protein evolutionary rates were positively correlated with transcriptomic and proteomic abundances, and the most abundant proteins showed positive selection. This pattern holds with the addition of four other published crotaline transcriptomes, from two more genera, and also for the recently published king cobra genome, suggesting that rapid evolution of abundant proteins may be generally true for snake venoms. Looking more broadly at Protobothrops, we show that rapid evolution of the most abundant components is due to positive selection, suggesting an interplay between abundance and adaptation. Given log-scale differences in toxin abundance, which are likely correlated with biosynthetic costs, we hypothesize that as a result of natural selection, snakes optimize return on energetic investment by producing more of venom proteins that increase their fitness. Natural selection then acts on the additive genetic variance of these components, in proportion to their contributions to overall fitness. Adaptive evolution of venoms may occur most rapidly through changes in expression levels that alter fitness contributions, and thus the strength of selection acting on specific secretome components.

Integrated proteomic and transcriptomic analysis of the Aedes aegypti eggshell

PubMed Central

2014-01-01

Background Mosquito eggshells show remarkable diversity in physical properties and structure consistent with adaptations to the wide variety of environments exploited by these insects. We applied proteomic, transcriptomic, and hybridization in situ techniques to identify gene products and pathways that participate in the assembly of the Aedes aegypti eggshell. Aedes aegypti population density is low during cold and dry seasons and increases immediately after rainfall. The survival of embryos through unfavorable periods is a key factor in the persistence of their populations. The work described here supports integrated vector control approaches that target eggshell formation and result in Ae. aegypti drought-intolerant phenotypes for public health initiatives directed to reduce mosquito-borne diseases. Results A total of 130 proteins were identified from the combined mass spectrometric analyses of eggshell preparations. Conclusions Classification of proteins according to their known and putative functions revealed the complexity of the eggshell structure. Three novel Ae. aegypti vitelline membrane proteins were discovered. Odorant-binding and cysteine-rich proteins that may be structural components of the eggshell were identified. Enzymes with peroxidase, laccase and phenoloxidase activities also were identified, and their likely involvements in cross-linking reactions that stabilize the eggshell structure are discussed. PMID:24707823

High-confidence coding and noncoding transcriptome maps

PubMed Central

2017-01-01

The advent of high-throughput RNA sequencing (RNA-seq) has led to the discovery of unprecedentedly immense transcriptomes encoded by eukaryotic genomes. However, the transcriptome maps are still incomplete partly because they were mostly reconstructed based on RNA-seq reads that lack their orientations (known as unstranded reads) and certain boundary information. Methods to expand the usability of unstranded RNA-seq data by predetermining the orientation of the reads and precisely determining the boundaries of assembled transcripts could significantly benefit the quality of the resulting transcriptome maps. Here, we present a high-performing transcriptome assembly pipeline, called CAFE, that significantly improves the original assemblies, respectively assembled with stranded and/or unstranded RNA-seq data, by orienting unstranded reads using the maximum likelihood estimation and by integrating information about transcription start sites and cleavage and polyadenylation sites. Applying large-scale transcriptomic data comprising 230 billion RNA-seq reads from the ENCODE, Human BodyMap 2.0, The Cancer Genome Atlas, and GTEx projects, CAFE enabled us to predict the directions of about 220 billion unstranded reads, which led to the construction of more accurate transcriptome maps, comparable to the manually curated map, and a comprehensive lncRNA catalog that includes thousands of novel lncRNAs. Our pipeline should not only help to build comprehensive, precise transcriptome maps from complex genomes but also to expand the universe of noncoding genomes. PMID:28396519

clusterProfiler: an R package for comparing biological themes among gene clusters.

PubMed

Yu, Guangchuang; Wang, Li-Gen; Han, Yanyan; He, Qing-Yu

2012-05-01

Increasing quantitative data generated from transcriptomics and proteomics require integrative strategies for analysis. Here, we present an R package, clusterProfiler that automates the process of biological-term classification and the enrichment analysis of gene clusters. The analysis module and visualization module were combined into a reusable workflow. Currently, clusterProfiler supports three species, including humans, mice, and yeast. Methods provided in this package can be easily extended to other species and ontologies. The clusterProfiler package is released under Artistic-2.0 License within Bioconductor project. The source code and vignette are freely available at http://bioconductor.org/packages/release/bioc/html/clusterProfiler.html.

Transcriptome and proteomic analyses reveal multiple differences associated with chloroplast development in the spaceflight-induced wheat albino mutant mta.

PubMed

Shi, Kui; Gu, Jiayu; Guo, Huijun; Zhao, Linshu; Xie, Yongdun; Xiong, Hongchun; Li, Junhui; Zhao, Shirong; Song, Xiyun; Liu, Luxiang

2017-01-01

Chloroplast development is an integral part of plant survival and growth, and occurs in parallel with chlorophyll biosynthesis. However, little is known about the mechanisms underlying chloroplast development in hexaploid wheat. Here, we obtained a spaceflight-induced wheat albino mutant mta. Chloroplast ultra-structural observation showed that chloroplasts of mta exhibit abnormal morphology and distribution compared to wild type. Photosynthetic pigments content was also significantly decreased in mta. Transcriptome and chloroplast proteome profiling of mta and wild type were done to identify differentially expressed genes (DEGs) and proteins (DEPs), respectively. In total 4,588 DEGs including 1,980 up- and 2,608 down-regulated, and 48 chloroplast DEPs including 15 up- and 33 down-regulated were identified in mta. Classification of DEGs revealed that most were involved in chloroplast development, chlorophyll biosynthesis, or photosynthesis. Besides, transcription factors such as PIF3, GLK and MYB which might participate in those pathways were also identified. The correlation analysis between DEGs and DEPs revealed that the transcript-to-protein in abundance was functioned into photosynthesis and chloroplast relevant groups. Real time qPCR analysis validated that the expression level of genes encoding photosynthetic proteins was significantly decreased in mta. Together, our results suggest that the molecular mechanism for albino leaf color formation in mta is a thoroughly regulated and complicated process. The combined analysis of transcriptome and proteome afford comprehensive information for further research on chloroplast development mechanism in wheat. And spaceflight provides a potential means for mutagenesis in crop breeding.

Mechanisms of CCl4-induced liver fibrosis with combined transcriptomic and proteomic analysis.

PubMed

Dong, Shu; Chen, Qi-Long; Song, Ya-Nan; Sun, Yang; Wei, Bin; Li, Xiao-Yan; Hu, Yi-Yang; Liu, Ping; Su, Shi-Bing

2016-01-01

The classic toxicity of carbon tetrachloride (CCl4) is to induce liver lesion and liver fibrosis. Liver fibrosis is a consequence of chronic liver lesion, which can progress into liver cirrhosis even hepatocarcinoma. However, the toxicological mechanisms of CCl4-induced liver fibrosis remain not fully understood. We combined transcriptomic and proteomic analysis and biological network technology, predicted toxicological targets and regulatory networks of CCl4 in liver fibrosis. Wistar rats were treated with CCl4 for 9 weeks. Histopathological changes, hydroxyproline (Hyp) contents, serum ALT and AST in the CCl4-treated group were significantly higher than that of CCl4-untreated group. CCl4-treated and -untreated liver tissues were examined by microarray and iTRAQ. The results showed that 3535 genes (fold change ≥ 1.5, P < 0.05) and 1412 proteins (fold change ≥ 1.2, P < 0.05) were differentially expressed. Moreover, the integrative analysis of transcriptomics and proteomics data showed 523 overlapped proteins, enriched in 182 GO terms including oxidation reduction, response to oxidative stress, inflammatory response, extracellular matrix organization, etc. Furthermore, KEGG pathway analysis showed that 36 pathways including retinol metabolism, PPAR signaling pathway, glycolysis/gluconeogenesis, arachidonic acid metabolism, metabolism of xenobiotics by cytochrome P450 and drug metabolism. Network of protein-protein interaction (PPI) and key function with their related targets were performed and the degree of network was calculated with Cytoscape. The expression of key targets such as CYP4A3, ALDH2 and ALDH7A1 decreased after CCl4 treatment. Therefore, the toxicological mechanisms of CCl4-induced liver fibrosis may be related with multi biological process, pathway and targets which may provide potential protection reaction mechanism for CCl4 detoxication in the liver.

De novo transcriptome sequencing of black pepper (Piper nigrum L.) and an analysis of genes involved in phenylpropanoid metabolism in response to Phytophthora capsici.

PubMed

Hao, Chaoyun; Xia, Zhiqiang; Fan, Rui; Tan, Lehe; Hu, Lisong; Wu, Baoduo; Wu, Huasong

2016-10-21

Piper nigrum L., or "black pepper", is an economically important spice crop in tropical regions. Black pepper production is markedly affected by foot rot disease caused by Phytophthora capsici, and genetic improvement of black pepper is essential for combating foot rot diseases. However, little is known about the mechanism of anti- P. capsici in black pepper. The molecular mechanisms underlying foot rot susceptibility were studied by comparing transcriptome analysis between resistant (Piper flaviflorum) and susceptible (Piper nigrum cv. Reyin-1) black pepper species. 116,432 unigenes were acquired from six libraries (three replicates of resistant and susceptible black pepper samples), which were integrated by applying BLAST similarity searches and noted by adopting Kyoto Encyclopaedia of Genes and Gene Ontology (GO) genome orthology identifiers. The reference transcriptome was mapped using two sets of digital gene expression data. Using GO enrichment analysis for the differentially expressed genes, the majority of the genes associated with the phenylpropanoid biosynthesis pathway were identified in P. flaviflorum. In addition, the expression of genes revealed that after susceptible and resistant species were inoculated with P. capsici, the majority of genes incorporated in the phenylpropanoid metabolism pathway were up-regulated in both species. Among various treatments and organs, all the genes were up-regulated to a relatively high degree in resistant species. Phenylalanine ammonia lyase and peroxidase enzyme activity increased in susceptible and resistant species after inoculation with P. capsici, and the resistant species increased faster. The resistant plants retain their vascular structure in lignin revealed by histochemical analysis. Our data provide critical information regarding target genes and a technological basis for future studies of black pepper genetic improvements, including transgenic breeding.

Analysis of de novo sequencing and transcriptome assembly and lignocellulolytic enzymes gene expression of Coriolopsis gallica HTC.

PubMed

Chen, Yuehong; Cao, Qinghua; Tao, Xiang; Shao, Huanhuan; Zhang, Kun; Zhang, Yizheng; Tan, Xuemei

2017-03-01

White-rot basidiomycete Coriolopsis gallica HTC is one of the main biodegraders of poplar. In our previous study, we have shown the strong capacity of C. gallica HTC to degrade lignocellulose. In this study, equal amounts of total RNA fromC. Gallica HTC cultures grown in different conditions were pooled together. Illumina paired-end RNA sequencing was performed, and 13.2 million 90-bp paired-end reads were generated. We chose the Merged Assembly of Oases data-set for the following blast searches and gene ontology analyses. The reads were assembled de novo into 28,034 transcripts (≥ 100 bp) using combined assembly strategy MAO. The transcripts were annotated using Blast2GO. In all, 18,810 transcripts (≥100 bp) achieved BLASTX hits, of which, 7048 transcripts had GO term and 2074 had ECs. The expression level of 11 lignocellulolytic enzyme genes from the assembled C. gallica HTC transcriptome were detected by real-time quantitative polymerase chain reaction. The results showed that expression levels of these genes were affected by carbon source and nitrogen source at the level of transcription. The current abundant transcriptome data allowed the identification of many new transcripts in C. gallica HTC. Data provided here represent the most comprehensive and integrated genomic resources for cloning and identifying genes of interest from C. gallica HTC. Characterization of C. gallica HTC transcriptome provides an effective tool to understand mechanisms underlying cellular and molecular functions of C. gallica HTC.

PeanutDB: an integrated bioinformatics web portal for Arachis hypogaea transcriptomics

PubMed Central

2012-01-01

Background The peanut (Arachis hypogaea) is an important crop cultivated worldwide for oil production and food sources. Its complex genetic architecture (e.g., the large and tetraploid genome possibly due to unique cross of wild diploid relatives and subsequent chromosome duplication: 2n = 4x = 40, AABB, 2800 Mb) presents a major challenge for its genome sequencing and makes it a less-studied crop. Without a doubt, transcriptome sequencing is the most effective way to harness the genome structure and gene expression dynamics of this non-model species that has a limited genomic resource. Description With the development of next generation sequencing technologies such as 454 pyro-sequencing and Illumina sequencing by synthesis, the transcriptomics data of peanut is rapidly accumulated in both the public databases and private sectors. Integrating 187,636 Sanger reads (103,685,419 bases), 1,165,168 Roche 454 reads (333,862,593 bases) and 57,135,995 Illumina reads (4,073,740,115 bases), we generated the first release of our peanut transcriptome assembly that contains 32,619 contigs. We provided EC, KEGG and GO functional annotations to these contigs and detected SSRs, SNPs and other genetic polymorphisms for each contig. Based on both open-source and our in-house tools, PeanutDB presents many seamlessly integrated web interfaces that allow users to search, filter, navigate and visualize easily the whole transcript assembly, its annotations and detected polymorphisms and simple sequence repeats. For each contig, sequence alignment is presented in both bird’s-eye view and nucleotide level resolution, with colorfully highlighted regions of mismatches, indels and repeats that facilitate close examination of assembly quality, genetic polymorphisms, sequence repeats and/or sequencing errors. Conclusion As a public genomic database that integrates peanut transcriptome data from different sources, PeanutDB (http://bioinfolab.muohio.edu/txid3818v1) provides the Peanut research community with an easy-to-use web portal that will definitely facilitate genomics research and molecular breeding in this less-studied crop. PMID:22712730

Root Type-Specific Reprogramming of Maize Pericycle Transcriptomes by Local High Nitrate Results in Disparate Lateral Root Branching Patterns1[OPEN

PubMed Central

Lithio, Andrew

2016-01-01

The adaptability of root system architecture to unevenly distributed mineral nutrients in soil is a key determinant of plant performance. The molecular mechanisms underlying nitrate dependent plasticity of lateral root branching across the different root types of maize are only poorly understood. In this study, detailed morphological and anatomical analyses together with cell type-specific transcriptome profiling experiments combining laser capture microdissection with RNA-seq were performed to unravel the molecular signatures of lateral root formation in primary, seminal, crown, and brace roots of maize (Zea mays) upon local high nitrate stimulation. The four maize root types displayed divergent branching patterns of lateral roots upon local high nitrate stimulation. In particular, brace roots displayed an exceptional architectural plasticity compared to other root types. Transcriptome profiling revealed root type-specific transcriptomic reprogramming of pericycle cells upon local high nitrate stimulation. The alteration of the transcriptomic landscape of brace root pericycle cells in response to local high nitrate stimulation was most significant. Root type-specific transcriptome diversity in response to local high nitrate highlighted differences in the functional adaptability and systemic shoot nitrogen starvation response during development. Integration of morphological, anatomical, and transcriptomic data resulted in a framework underscoring similarity and diversity among root types grown in heterogeneous nitrate environments. PMID:26811190

Transcriptome analysis during ripening of table grape berry cv. Thompson Seedless

PubMed Central

Balic, Iván; Vizoso, Paula; Nilo-Poyanco, Ricardo; Sanhueza, Dayan; Olmedo, Patricio; Sepúlveda, Pablo; Arriagada, Cesar; Defilippi, Bruno G.; Meneses, Claudio

2018-01-01

Ripening is one of the key processes associated with the development of major organoleptic characteristics of the fruit. This process has been extensively characterized in climacteric fruit, in contrast with non-climacteric fruit such as grape, where the process is less understood. With the aim of studying changes in gene expression during ripening of non-climacteric fruit, an Illumina based RNA-Seq transcriptome analysis was performed on four developmental stages, between veraison and harvest, on table grapes berries cv Thompson Seedless. Functional analysis showed a transcriptional increase in genes related with degradation processes of chlorophyll, lipids, macromolecules recycling and nucleosomes organization; accompanied by a decrease in genes related with chloroplasts integrity and amino acid synthesis pathways. It was possible to identify several processes described during leaf senescence, particularly close to harvest. Before this point, the results suggest a high transcriptional activity associated with the regulation of gene expression, cytoskeletal organization and cell wall metabolism, which can be related to growth of berries and firmness loss characteristic to this stage of development. This high metabolic activity could be associated with an increase in the transcription of genes related with glycolysis and respiration, unexpected for a non-climacteric fruit ripening. PMID:29320527

Transcriptome analysis during ripening of table grape berry cv. Thompson Seedless.

PubMed

Balic, Iván; Vizoso, Paula; Nilo-Poyanco, Ricardo; Sanhueza, Dayan; Olmedo, Patricio; Sepúlveda, Pablo; Arriagada, Cesar; Defilippi, Bruno G; Meneses, Claudio; Campos-Vargas, Reinaldo

2018-01-01

Ripening is one of the key processes associated with the development of major organoleptic characteristics of the fruit. This process has been extensively characterized in climacteric fruit, in contrast with non-climacteric fruit such as grape, where the process is less understood. With the aim of studying changes in gene expression during ripening of non-climacteric fruit, an Illumina based RNA-Seq transcriptome analysis was performed on four developmental stages, between veraison and harvest, on table grapes berries cv Thompson Seedless. Functional analysis showed a transcriptional increase in genes related with degradation processes of chlorophyll, lipids, macromolecules recycling and nucleosomes organization; accompanied by a decrease in genes related with chloroplasts integrity and amino acid synthesis pathways. It was possible to identify several processes described during leaf senescence, particularly close to harvest. Before this point, the results suggest a high transcriptional activity associated with the regulation of gene expression, cytoskeletal organization and cell wall metabolism, which can be related to growth of berries and firmness loss characteristic to this stage of development. This high metabolic activity could be associated with an increase in the transcription of genes related with glycolysis and respiration, unexpected for a non-climacteric fruit ripening.

Metabolic reprogramming and dependencies associated with epithelial cancer stem cells independent of the epithelial-mesenchymal transition program

PubMed Central

Aguilar, Esther; de Mas, Igor Marin; Zodda, Erika; Marin, Silvia; Morrish, Fionnuala; Selivanov, Vitaly; Meca-Cortés, Óscar; Delowar, Hossain; Pons, Mònica; Izquierdo, Inés; Celià-Terrassa, Toni; de Atauri, Pedro; Centelles, Josep J; Hockenbery, David; Thomson, Timothy M; Cascante, Marta

2016-01-01

In solid tumors, cancer stem cells (CSCs) can arise independently of epithelial-mesenchymal transition (EMT). In spite of recent efforts, the metabolic reprogramming associated with CSC phenotypes uncoupled from EMT is poorly understood. Here, by using metabolomic and fluxomic approaches, we identify major metabolic profiles that differentiate metastatic prostate epithelial CSCs (e-CSCs) from non-CSCs expressing a stable EMT. We have found that the e-CSC program in our cellular model is characterized by a high plasticity in energy substrate metabolism, including an enhanced Warburg effect, a greater carbon and energy source flexibility driven by fatty acids and amino acid metabolism and an essential reliance on the proton buffering capacity conferred by glutamine metabolism. An analysis of transcriptomic data yielded a metabolic gene signature for our e-CSCs consistent with the metabolomics and fluxomics analysis that correlated with tumor progression and metastasis in prostate cancer and in 11 additional cancer types. Interestingly, an integrated metabolomics, fluxomics and transcriptomics analysis allowed us to identify key metabolic players regulated at the post-transcriptional level, suggesting potential biomarkers and therapeutic targets to effectively forestall metastasis. PMID:27146024

MinOmics, an Integrative and Immersive Tool for Multi-Omics Analysis.

PubMed

Maes, Alexandre; Martinez, Xavier; Druart, Karen; Laurent, Benoist; Guégan, Sean; Marchand, Christophe H; Lemaire, Stéphane D; Baaden, Marc

2018-06-21

Proteomic and transcriptomic technologies resulted in massive biological datasets, their interpretation requiring sophisticated computational strategies. Efficient and intuitive real-time analysis remains challenging. We use proteomic data on 1417 proteins of the green microalga Chlamydomonas reinhardtii to investigate physicochemical parameters governing selectivity of three cysteine-based redox post translational modifications (PTM): glutathionylation (SSG), nitrosylation (SNO) and disulphide bonds (SS) reduced by thioredoxins. We aim to understand underlying molecular mechanisms and structural determinants through integration of redox proteome data from gene- to structural level. Our interactive visual analytics approach on an 8.3 m2 display wall of 25 MPixel resolution features stereoscopic three dimensions (3D) representation performed by UnityMol WebGL. Virtual reality headsets complement the range of usage configurations for fully immersive tasks. Our experiments confirm that fast access to a rich cross-linked database is necessary for immersive analysis of structural data. We emphasize the possibility to display complex data structures and relationships in 3D, intrinsic to molecular structure visualization, but less common for omics-network analysis. Our setup is powered by MinOmics, an integrated analysis pipeline and visualization framework dedicated to multi-omics analysis. MinOmics integrates data from various sources into a materialized physical repository. We evaluate its performance, a design criterion for the framework.

A conserved BDNF, glutamate- and GABA-enriched gene module related to human depression identified by coexpression meta-analysis and DNA variant genome-wide association studies.

PubMed

Chang, Lun-Ching; Jamain, Stephane; Lin, Chien-Wei; Rujescu, Dan; Tseng, George C; Sibille, Etienne

2014-01-01

Large scale gene expression (transcriptome) analysis and genome-wide association studies (GWAS) for single nucleotide polymorphisms have generated a considerable amount of gene- and disease-related information, but heterogeneity and various sources of noise have limited the discovery of disease mechanisms. As systematic dataset integration is becoming essential, we developed methods and performed meta-clustering of gene coexpression links in 11 transcriptome studies from postmortem brains of human subjects with major depressive disorder (MDD) and non-psychiatric control subjects. We next sought enrichment in the top 50 meta-analyzed coexpression modules for genes otherwise identified by GWAS for various sets of disorders. One coexpression module of 88 genes was consistently and significantly associated with GWAS for MDD, other neuropsychiatric disorders and brain functions, and for medical illnesses with elevated clinical risk of depression, but not for other diseases. In support of the superior discriminative power of this novel approach, we observed no significant enrichment for GWAS-related genes in coexpression modules extracted from single studies or in meta-modules using gene expression data from non-psychiatric control subjects. Genes in the identified module encode proteins implicated in neuronal signaling and structure, including glutamate metabotropic receptors (GRM1, GRM7), GABA receptors (GABRA2, GABRA4), and neurotrophic and development-related proteins [BDNF, reelin (RELN), Ephrin receptors (EPHA3, EPHA5)]. These results are consistent with the current understanding of molecular mechanisms of MDD and provide a set of putative interacting molecular partners, potentially reflecting components of a functional module across cells and biological pathways that are synchronously recruited in MDD, other brain disorders and MDD-related illnesses. Collectively, this study demonstrates the importance of integrating transcriptome data, gene coexpression modules and GWAS results for providing novel and complementary approaches to investigate the molecular pathology of MDD and other complex brain disorders.

Integrated application of transcriptomics and metabolomics provides insights into glycogen content regulation in the Pacific oyster Crassostrea gigas.

PubMed

Li, Busu; Song, Kai; Meng, Jie; Li, Li; Zhang, Guofan

2017-09-11

The Pacific oyster Crassostrea gigas is an important marine fishery resource, which contains high levels of glycogen that contributes to the flavor and the quality of the oyster. However, little is known about the molecular and chemical mechanisms underlying glycogen content differences in Pacific oysters. Using a homogeneous cultured Pacific oyster family, we explored these regulatory networks at the level of the metabolome and the transcriptome. Oysters with the highest and lowest natural glycogen content were selected for differential transcriptome and metabolome analysis. We identified 1888 differentially-expressed genes, seventy-five differentially-abundant metabolites, which are part of twenty-seven signaling pathways that were enriched using an integrated analysis of the interaction between the differentially-expressed genes and the differentially-abundant metabolites. Based on these results, we found that a high expression of carnitine O-palmitoyltransferase 2 (CPT2), indicative of increased fatty acid degradation, is associated with a lower glycogen content. Together, a high level of expression of phosphoenolpyruvate carboxykinase (PEPCK), and high levels of glucogenic amino acids likely underlie the increased glycogen production in high-glycogen oysters. In addition, the higher levels of the glycolytic enzymes hexokinase (HK) and pyruvate kinase (PK), as well as of the TCA cycle enzymes malate dehydrogenase (MDH) and pyruvate carboxylase (PYC), imply that there is a concomitant up-regulation of energy metabolism in high-glycogen oysters. High-glycogen oysters also appeared to have an increased ability to cope with stress, since the levels of the antioxidant glutathione peroxidase enzyme 5 (GPX5) gene were also increased. Our results suggest that amino acids and free fatty acids are closely related to glycogen content in oysters. In addition, oysters with a high glycogen content have a greater energy production capacity and a greater ability to cope with stress. These findings will not only provide insights into the molecular mechanisms underlying oyster quality, but also promote research into the molecular breeding of oysters.

Analysis of the Citrullus colocynthis Transcriptome during Water Deficit Stress

PubMed Central

Wang, Zhuoyu; Hu, Hongtao; Goertzen, Leslie R.; McElroy, J. Scott; Dane, Fenny

2014-01-01

Citrullus colocynthis is a very drought tolerant species, closely related to watermelon (C. lanatus var. lanatus), an economically important cucurbit crop. Drought is a threat to plant growth and development, and the discovery of drought inducible genes with various functions is of great importance. We used high throughput mRNA Illumina sequencing technology and bioinformatic strategies to analyze the C. colocynthis leaf transcriptome under drought treatment. Leaf samples at four different time points (0, 24, 36, or 48 hours of withholding water) were used for RNA extraction and Illumina sequencing. qRT-PCR of several drought responsive genes was performed to confirm the accuracy of RNA sequencing. Leaf transcriptome analysis provided the first glimpse of the drought responsive transcriptome of this unique cucurbit species. A total of 5038 full-length cDNAs were detected, with 2545 genes showing significant changes during drought stress. Principle component analysis indicated that drought was the major contributing factor regulating transcriptome changes. Up regulation of many transcription factors, stress signaling factors, detoxification genes, and genes involved in phytohormone signaling and citrulline metabolism occurred under the water deficit conditions. The C. colocynthis transcriptome data highlight the activation of a large set of drought related genes in this species, thus providing a valuable resource for future functional analysis of candidate genes in defense of drought stress. PMID:25118696

Cancer Transcriptome Dataset Analysis: Comparing Methods of Pathway and Gene Regulatory Network-Based Cluster Identification.

PubMed

Nam, Seungyoon

2017-04-01

Cancer transcriptome analysis is one of the leading areas of Big Data science, biomarker, and pharmaceutical discovery, not to forget personalized medicine. Yet, cancer transcriptomics and postgenomic medicine require innovation in bioinformatics as well as comparison of the performance of available algorithms. In this data analytics context, the value of network generation and algorithms has been widely underscored for addressing the salient questions in cancer pathogenesis. Analysis of cancer trancriptome often results in complicated networks where identification of network modularity remains critical, for example, in delineating the "druggable" molecular targets. Network clustering is useful, but depends on the network topology in and of itself. Notably, the performance of different network-generating tools for network cluster (NC) identification has been little investigated to date. Hence, using gastric cancer (GC) transcriptomic datasets, we compared two algorithms for generating pathway versus gene regulatory network-based NCs, showing that the pathway-based approach better agrees with a reference set of cancer-functional contexts. Finally, by applying pathway-based NC identification to GC transcriptome datasets, we describe cancer NCs that associate with candidate therapeutic targets and biomarkers in GC. These observations collectively inform future research on cancer transcriptomics, drug discovery, and rational development of new analysis tools for optimal harnessing of omics data.

Integrated mRNA and microRNA transcriptome analyses reveal regulation of thermal acclimation in Gymnocypris przewalskii: A case study in Tibetan Schizothoracine fish

PubMed Central

Tian, Fei; Zhao, Kai

2017-01-01

Environmental acclimation is important episode in wildlife occupation of the high-altitude Tibetan Plateau (TP). Transcriptome-wide studies on thermal acclimation mechanism in fish species are rarely revealed in Tibetan Plateau fish at high altitude. Thus, we used mRNA and miRNA transcriptome sequencing to investigate regulation of thermal acclimation in larval Tibetan naked carp, Gymnocypris przewalskii. We first remodeled the regulation network of mRNA and miRNA in thermal acclimation, and then identified differential expression of miRNAs and target mRNAs enriched in metabolic and digestive pathways. Interestingly, we identified two candidate genes contributed to normal skeletal development. The altered expression of these gene groups could potentially be associated with the developmental issues of deformity and induced larval death. Our results have three important implications: first, these findings provide strong evidences to support our hypothesis that G. przewalskii possess ability to build heat-tolerance against the controversial issue. Second, this study shows that transcriptional and post-transcriptional regulations are extensively involved in thermal acclimation. Third, the integrated mRNA and microRNA transcriptome analyses provide a large number of valuable genetic resources for future studies on environmental stress response in G. przewalskii and as a case study in Tibetan Schizothoracine fish. PMID:29045433

A Comprehensive Transcriptomic and Proteomic Analysis of Hydra Head Regeneration.

PubMed

Petersen, Hendrik O; Höger, Stefanie K; Looso, Mario; Lengfeld, Tobias; Kuhn, Anne; Warnken, Uwe; Nishimiya-Fujisawa, Chiemi; Schnölzer, Martina; Krüger, Marcus; Özbek, Suat; Simakov, Oleg; Holstein, Thomas W

2015-08-01

The cnidarian freshwater polyp Hydra sp. exhibits an unparalleled regeneration capacity in the animal kingdom. Using an integrative transcriptomic and stable isotope labeling by amino acids in cell culture proteomic/phosphoproteomic approach, we studied stem cell-based regeneration in Hydra polyps. As major contributors to head regeneration, we identified diverse signaling pathways adopted for the regeneration response as well as enriched novel genes. Our global analysis reveals two distinct molecular cascades: an early injury response and a subsequent, signaling driven patterning of the regenerating tissue. A key factor of the initial injury response is a general stabilization of proteins and a net upregulation of transcripts, which is followed by a subsequent activation cascade of signaling molecules including Wnts and transforming growth factor (TGF) beta-related factors. We observed moderate overlap between the factors contributing to proteomic and transcriptomic responses suggesting a decoupled regulation between the transcriptional and translational levels. Our data also indicate that interstitial stem cells and their derivatives (e.g., neurons) have no major role in Hydra head regeneration. Remarkably, we found an enrichment of evolutionarily more recent genes in the early regeneration response, whereas conserved genes are more enriched in the late phase. In addition, genes specific to the early injury response were enriched in transposon insertions. Genetic dynamicity and taxon-specific factors might therefore play a hitherto underestimated role in Hydra regeneration. © The Author 2015. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

Reptilian Transcriptomes v2.0: An Extensive Resource for Sauropsida Genomics and Transcriptomics

PubMed Central

Tzika, Athanasia C.; Ullate-Agote, Asier; Grbic, Djordje; Milinkovitch, Michel C.

2015-01-01

Despite the availability of deep-sequencing techniques, genomic and transcriptomic data remain unevenly distributed across phylogenetic groups. For example, reptiles are poorly represented in sequence databases, hindering functional evolutionary and developmental studies in these lineages substantially more diverse than mammals. In addition, different studies use different assembly and annotation protocols, inhibiting meaningful comparisons. Here, we present the “Reptilian Transcriptomes Database 2.0,” which provides extensive annotation of transcriptomes and genomes from species covering the major reptilian lineages. To this end, we sequenced normalized complementary DNA libraries of multiple adult tissues and various embryonic stages of the leopard gecko and the corn snake and gathered published reptilian sequence data sets from representatives of the four extant orders of reptiles: Squamata (snakes and lizards), the tuatara, crocodiles, and turtles. The LANE runner 2.0 software was implemented to annotate all assemblies within a single integrated pipeline. We show that this approach increases the annotation completeness of the assembled transcriptomes/genomes. We then built large concatenated protein alignments of single-copy genes and inferred phylogenetic trees that support the positions of turtles and the tuatara as sister groups of Archosauria and Squamata, respectively. The Reptilian Transcriptomes Database 2.0 resource will be updated to include selected new data sets as they become available, thus making it a reference for differential expression studies, comparative genomics and transcriptomics, linkage mapping, molecular ecology, and phylogenomic analyses involving reptiles. The database is available at www.reptilian-transcriptomes.org and can be enquired using a wwwblast server installed at the University of Geneva. PMID:26133641

Toxicogenomics in Environmental Science.

PubMed

Brinke, Alexandra; Buchinger, Sebastian

This chapter reviews the current knowledge and recent progress in the field of environmental, aquatic ecotoxicogenomics with a focus on transcriptomic methods. In ecotoxicogenomics the omics technologies are applied for the detection and assessment of adverse effects in the environment, and thus are to be distinguished from omics used in human toxicology [Snape et al., Aquat Toxicol 67:143-154, 2004]. Transcriptomic methods in ecotoxicology are applied to gain a mechanistic understanding of toxic effects on organisms or populations, and thus aim to bridge the gap between cause and effect. A worthwhile effect-based interpretation of stressor induced changes on the transcriptome is based on the principle of phenotypic-anchoring [Paules, Environ Health Perspect 111:A338-A339, 2003]. Thereby, changes on the transcriptomic level can only be identified as effects if they are clearly linked to a specific stressor-induced effect on the macroscopic level. By integrating those macroscopic and transcriptomic effects, conclusions on the effect-inducing type of the stressor can be drawn. Stressor-specific effects on the transcriptomic level can be identified as stressor-specific induced pathways, transcriptomic patterns, or stressors-specific genetic biomarkers. In this chapter, examples of the combined application of macroscopic and transcriptional effects for the identification of environmental stressors, such as aquatic pollutants, are given and discussed. By means of these examples, challenges on the way to a standardized application of transcriptomics in ecotoxicology are discussed. This is also done against the background of the application of transcriptomic methods in environmental regulation such as the EU regulation Registration, Evaluation, Authorisation and Restriction of Chemicals (REACH).

Quantitative RNA-seq analysis of the Campylobacter jejuni transcriptome

PubMed Central

Chaudhuri, Roy R.; Yu, Lu; Kanji, Alpa; Perkins, Timothy T.; Gardner, Paul P.; Choudhary, Jyoti; Maskell, Duncan J.

2011-01-01

Campylobacter jejuni is the most common bacterial cause of foodborne disease in the developed world. Its general physiology and biochemistry, as well as the mechanisms enabling it to colonize and cause disease in various hosts, are not well understood, and new approaches are required to understand its basic biology. High-throughput sequencing technologies provide unprecedented opportunities for functional genomic research. Recent studies have shown that direct Illumina sequencing of cDNA (RNA-seq) is a useful technique for the quantitative and qualitative examination of transcriptomes. In this study we report RNA-seq analyses of the transcriptomes of C. jejuni (NCTC11168) and its rpoN mutant. This has allowed the identification of hitherto unknown transcriptional units, and further defines the regulon that is dependent on rpoN for expression. The analysis of the NCTC11168 transcriptome was supplemented by additional proteomic analysis using liquid chromatography-MS. The transcriptomic and proteomic datasets represent an important resource for the Campylobacter research community. PMID:21816880

Updated Rice Kinase Database RKD 2.0: enabling transcriptome and functional analysis of rice kinase genes.

PubMed

Chandran, Anil Kumar Nalini; Yoo, Yo-Han; Cao, Peijian; Sharma, Rita; Sharma, Manoj; Dardick, Christopher; Ronald, Pamela C; Jung, Ki-Hong

2016-12-01

Protein kinases catalyze the transfer of a phosphate moiety from a phosphate donor to the substrate molecule, thus playing critical roles in cell signaling and metabolism. Although plant genomes contain more than 1000 genes that encode kinases, knowledge is limited about the function of each of these kinases. A major obstacle that hinders progress towards kinase characterization is functional redundancy. To address this challenge, we previously developed the rice kinase database (RKD) that integrated omics-scale data within a phylogenetics context. An updated version of rice kinase database (RKD) that contains metadata derived from NCBI GEO expression datasets has been developed. RKD 2.0 facilitates in-depth transcriptomic analyses of kinase-encoding genes in diverse rice tissues and in response to biotic and abiotic stresses and hormone treatments. We identified 261 kinases specifically expressed in particular tissues, 130 that are significantly up- regulated in response to biotic stress, 296 in response to abiotic stress, and 260 in response to hormones. Based on this update and Pearson correlation coefficient (PCC) analysis, we estimated that 19 out of 26 genes characterized through loss-of-function studies confer dominant functions. These were selected because they either had paralogous members with PCC values of <0.5 or had no paralog. Compared with the previous version of RKD, RKD 2.0 enables more effective estimations of functional redundancy or dominance because it uses comprehensive expression profiles rather than individual profiles. The integrated analysis of RKD with PCC establishes a single platform for researchers to select rice kinases for functional analyses.

Meta-Analysis of Global Transcriptomics Suggests that Conserved Genetic Pathways are Responsible for Quercetin and Tannic Acid Mediated Longevity in C. elegans

PubMed Central

Pietsch, Kerstin; Saul, Nadine; Swain, Suresh C.; Menzel, Ralph; Steinberg, Christian E. W.; Stürzenbaum, Stephen R.

2012-01-01

Recent research has highlighted that the polyphenols Quercetin and Tannic acid are capable of extending the lifespan of Caenorhabditis elegans. To gain a deep understanding of the underlying molecular genetics, we analyzed the global transcriptional patterns of nematodes exposed to three concentrations of Quercetin or Tannic acid, respectively. By means of an intricate meta-analysis it was possible to compare the transcriptomes of polyphenol exposure to recently published datasets derived from (i) longevity mutants or (ii) infection. This detailed comparative in silico analysis facilitated the identification of compound specific and overlapping transcriptional profiles and allowed the prediction of putative mechanistic models of Quercetin and Tannic acid mediated longevity. Lifespan extension due to Quercetin was predominantly driven by the metabolome, TGF-beta signaling, Insulin-like signaling, and the p38 MAPK pathway and Tannic acid’s impact involved, in part, the amino acid metabolism and was modulated by the TGF-beta and the p38 MAPK pathways. DAF-12, which integrates TGF-beta and Insulin-like downstream signaling, and genetic players of the p38 MAPK pathway therefore seem to be crucial regulators for both polyphenols. Taken together, this study underlines how meta-analyses can provide an insight of molecular events that go beyond the traditional categorization into gene ontology-terms and Kyoto encyclopedia of genes and genomes-pathways. It also supports the call to expand the generation of comparative and integrative databases, an effort that is currently still in its infancy. PMID:22493606

Identifying Molecular Effects of Diet through Systems Biology: Influence of Herring Diet on Sterol Metabolism and Protein Turnover in Mice

PubMed Central

Holmäng, Agneta; Sandberg, Ann-Sofie; Nielsen, Jens

2010-01-01

Background Changes in lifestyle have resulted in an epidemic development of obesity-related diseases that challenge the healthcare systems worldwide. To develop strategies to tackle this problem the focus is on diet to prevent the development of obesity-associated diseases such as cardiovascular disease (CVD). This will require methods for linking nutrient intake with specific metabolic processes in different tissues. Methodology/Principal Finding Low-density lipoprotein receptor-deficient (Ldlr −/−) mice were fed a high fat/high sugar diet to mimic a westernized diet, being a major reason for development of obesity and atherosclerosis. The diets were supplemented with either beef or herring, and matched in macronutrient contents. Body composition, plasma lipids and aortic lesion areas were measured. Transcriptomes of metabolically important tissues, e.g. liver, muscle and adipose tissue were analyzed by an integrated approach with metabolic networks to directly map the metabolic effects of diet in these different tissues. Our analysis revealed a reduction in sterol metabolism and protein turnover at the transcriptional level in herring-fed mice. Conclusion This study shows that an integrated analysis of transcriptome data using metabolic networks resulted in the identification of signature pathways. This could not have been achieved using standard clustering methods. In particular, this systems biology analysis could enrich the information content of biomedical or nutritional data where subtle changes in several tissues together affects body metabolism or disease progression. This could be applied to improve diets for subjects exposed to health risks associated with obesity. PMID:20808764

Analysis of Transcriptomic Dose Response Data in the ...

EPA Pesticide Factsheets

Slide presentation at the HESI-HEALTH Canada-McGill Workshop on Transcriptomic Dose Response Data in the Context of Chemical Risk Assessment Slide presentation at the HESI-HEALTH Canada-McGill Workshop on Transcriptomic Dose Response Data in the Context of Chemical Risk Assessment

Developmental Transcriptome for a Facultatively Eusocial Bee, Megalopta genalis

PubMed Central

Jones, Beryl M.; Wcislo, William T.; Robinson, Gene E.

2015-01-01

Transcriptomes provide excellent foundational resources for mechanistic and evolutionary analyses of complex traits. We present a developmental transcriptome for the facultatively eusocial bee Megalopta genalis, which represents a potential transition point in the evolution of eusociality. A de novo transcriptome assembly of Megalopta genalis was generated using paired-end Illumina sequencing and the Trinity assembler. Males and females of all life stages were aligned to this transcriptome for analysis of gene expression profiles throughout development. Gene Ontology analysis indicates that stage-specific genes are involved in ion transport, cell–cell signaling, and metabolism. A number of distinct biological processes are upregulated in each life stage, and transitions between life stages involve shifts in dominant functional processes, including shifts from transcriptional regulation in embryos to metabolism in larvae, and increased lipid metabolism in adults. We expect that this transcriptome will provide a useful resource for future analyses to better understand the molecular basis of the evolution of eusociality and, more generally, phenotypic plasticity. PMID:26276382

Developmental Transcriptome for a Facultatively Eusocial Bee, Megalopta genalis.

PubMed

Jones, Beryl M; Wcislo, William T; Robinson, Gene E

2015-08-14

Transcriptomes provide excellent foundational resources for mechanistic and evolutionary analyses of complex traits. We present a developmental transcriptome for the facultatively eusocial bee Megalopta genalis, which represents a potential transition point in the evolution of eusociality. A de novo transcriptome assembly of Megalopta genalis was generated using paired-end Illumina sequencing and the Trinity assembler. Males and females of all life stages were aligned to this transcriptome for analysis of gene expression profiles throughout development. Gene Ontology analysis indicates that stage-specific genes are involved in ion transport, cell-cell signaling, and metabolism. A number of distinct biological processes are upregulated in each life stage, and transitions between life stages involve shifts in dominant functional processes, including shifts from transcriptional regulation in embryos to metabolism in larvae, and increased lipid metabolism in adults. We expect that this transcriptome will provide a useful resource for future analyses to better understand the molecular basis of the evolution of eusociality and, more generally, phenotypic plasticity. Copyright © 2015 Jones et al.

A survey of the sorghum transcriptome using single-molecule long reads

DOE PAGES

Abdel-Ghany, Salah E.; Hamilton, Michael; Jacobi, Jennifer L.; ...

2016-06-24

Alternative splicing and alternative polyadenylation (APA) of pre-mRNAs greatly contribute to transcriptome diversity, coding capacity of a genome and gene regulatory mechanisms in eukaryotes. Second-generation sequencing technologies have been extensively used to analyse transcriptomes. However, a major limitation of short-read data is that it is difficult to accurately predict full-length splice isoforms. Here we sequenced the sorghum transcriptome using Pacific Biosciences single-molecule real-time long-read isoform sequencing and developed a pipeline called TAPIS (Transcriptome Analysis Pipeline for Isoform Sequencing) to identify full-length splice isoforms and APA sites. Our analysis reveals transcriptome-wide full-length isoforms at an unprecedented scale with over 11,000 novelmore » splice isoforms. Additionally, we uncover APA ofB11,000 expressed genes and more than 2,100 novel genes. Lastly, these results greatly enhance sorghum gene annotations and aid in studying gene regulation in this important bioenergy crop. The TAPIS pipeline will serve as a useful tool to analyse Iso-Seq data from any organism.« less

A survey of the sorghum transcriptome using single-molecule long reads

PubMed Central

Abdel-Ghany, Salah E.; Hamilton, Michael; Jacobi, Jennifer L.; Ngam, Peter; Devitt, Nicholas; Schilkey, Faye; Ben-Hur, Asa; Reddy, Anireddy S. N.

2016-01-01

Alternative splicing and alternative polyadenylation (APA) of pre-mRNAs greatly contribute to transcriptome diversity, coding capacity of a genome and gene regulatory mechanisms in eukaryotes. Second-generation sequencing technologies have been extensively used to analyse transcriptomes. However, a major limitation of short-read data is that it is difficult to accurately predict full-length splice isoforms. Here we sequenced the sorghum transcriptome using Pacific Biosciences single-molecule real-time long-read isoform sequencing and developed a pipeline called TAPIS (Transcriptome Analysis Pipeline for Isoform Sequencing) to identify full-length splice isoforms and APA sites. Our analysis reveals transcriptome-wide full-length isoforms at an unprecedented scale with over 11,000 novel splice isoforms. Additionally, we uncover APA of ∼11,000 expressed genes and more than 2,100 novel genes. These results greatly enhance sorghum gene annotations and aid in studying gene regulation in this important bioenergy crop. The TAPIS pipeline will serve as a useful tool to analyse Iso-Seq data from any organism. PMID:27339290

Transcriptome In Vivo Analysis (TIVA) of spatially defined single cells in intact live mouse and human brain tissue

PubMed Central

Lovatt, Ditte; Ruble, Brittani K.; Lee, Jaehee; Dueck, Hannah; Kim, Tae Kyung; Fisher, Stephen; Francis, Chantal; Spaethling, Jennifer M.; Wolf, John A.; Grady, M. Sean; Ulyanova, Alexandra V.; Yeldell, Sean B.; Griepenburg, Julianne C.; Buckley, Peter T.; Kim, Junhyong; Sul, Jai-Yoon; Dmochowski, Ivan J.; Eberwine, James

2014-01-01

Transcriptome profiling is an indispensable tool in advancing the understanding of single cell biology, but depends upon methods capable of isolating mRNA at the spatial resolution of a single cell. Current capture methods lack sufficient spatial resolution to isolate mRNA from individual in vivo resident cells without damaging adjacent tissue. Because of this limitation, it has been difficult to assess the influence of the microenvironment on the transcriptome of individual neurons. Here, we engineered a Transcriptome In Vivo Analysis (TIVA)-tag, which upon photoactivation enables mRNA capture from single cells in live tissue. Using the TIVA-tag in combination with RNA-seq to analyze transcriptome variance among single dispersed cells and in vivo resident mouse and human neurons, we show that the tissue microenvironment shapes the transcriptomic landscape of individual cells. The TIVA methodology provides the first noninvasive approach for capturing mRNA from single cells in their natural microenvironment. PMID:24412976

MicroScope-an integrated resource for community expertise of gene functions and comparative analysis of microbial genomic and metabolic data.

PubMed

Médigue, Claudine; Calteau, Alexandra; Cruveiller, Stéphane; Gachet, Mathieu; Gautreau, Guillaume; Josso, Adrien; Lajus, Aurélie; Langlois, Jordan; Pereira, Hugo; Planel, Rémi; Roche, David; Rollin, Johan; Rouy, Zoe; Vallenet, David

2017-09-12

The overwhelming list of new bacterial genomes becoming available on a daily basis makes accurate genome annotation an essential step that ultimately determines the relevance of thousands of genomes stored in public databanks. The MicroScope platform (http://www.genoscope.cns.fr/agc/microscope) is an integrative resource that supports systematic and efficient revision of microbial genome annotation, data management and comparative analysis. Starting from the results of our syntactic, functional and relational annotation pipelines, MicroScope provides an integrated environment for the expert annotation and comparative analysis of prokaryotic genomes. It combines tools and graphical interfaces to analyze genomes and to perform the manual curation of gene function in a comparative genomics and metabolic context. In this article, we describe the free-of-charge MicroScope services for the annotation and analysis of microbial (meta)genomes, transcriptomic and re-sequencing data. Then, the functionalities of the platform are presented in a way providing practical guidance and help to the nonspecialists in bioinformatics. Newly integrated analysis tools (i.e. prediction of virulence and resistance genes in bacterial genomes) and original method recently developed (the pan-genome graph representation) are also described. Integrated environments such as MicroScope clearly contribute, through the user community, to help maintaining accurate resources. © The Author 2017. Published by Oxford University Press.

PARRoT- a homology-based strategy to quantify and compare RNA-sequencing from non-model organisms.

PubMed

Gan, Ruei-Chi; Chen, Ting-Wen; Wu, Timothy H; Huang, Po-Jung; Lee, Chi-Ching; Yeh, Yuan-Ming; Chiu, Cheng-Hsun; Huang, Hsien-Da; Tang, Petrus

2016-12-22

Next-generation sequencing promises the de novo genomic and transcriptomic analysis of samples of interests. However, there are only a few organisms having reference genomic sequences and even fewer having well-defined or curated annotations. For transcriptome studies focusing on organisms lacking proper reference genomes, the common strategy is de novo assembly followed by functional annotation. However, things become even more complicated when multiple transcriptomes are compared. Here, we propose a new analysis strategy and quantification methods for quantifying expression level which not only generate a virtual reference from sequencing data, but also provide comparisons between transcriptomes. First, all reads from the transcriptome datasets are pooled together for de novo assembly. The assembled contigs are searched against NCBI NR databases to find potential homolog sequences. Based on the searched result, a set of virtual transcripts are generated and served as a reference transcriptome. By using the same reference, normalized quantification values including RC (read counts), eRPKM (estimated RPKM) and eTPM (estimated TPM) can be obtained that are comparable across transcriptome datasets. In order to demonstrate the feasibility of our strategy, we implement it in the web service PARRoT. PARRoT stands for Pipeline for Analyzing RNA Reads of Transcriptomes. It analyzes gene expression profiles for two transcriptome sequencing datasets. For better understanding of the biological meaning from the comparison among transcriptomes, PARRoT further provides linkage between these virtual transcripts and their potential function through showing best hits in SwissProt, NR database, assigning GO terms. Our demo datasets showed that PARRoT can analyze two paired-end transcriptomic datasets of approximately 100 million reads within just three hours. In this study, we proposed and implemented a strategy to analyze transcriptomes from non-reference organisms which offers the opportunity to quantify and compare transcriptome profiles through a homolog based virtual transcriptome reference. By using the homolog based reference, our strategy effectively avoids the problems that may cause from inconsistencies among transcriptomes. This strategy will shed lights on the field of comparative genomics for non-model organism. We have implemented PARRoT as a web service which is freely available at http://parrot.cgu.edu.tw .

Integrating Membrane Transport with Male Gametophyte Development and Function through Transcriptomics.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bock KW; D Honys; JM. Ward

Male fertility depends on the proper development of the male gametophyte, successful pollen germination, tube growth and delivery of the sperm cells to the ovule. Previous studies have shown that nutrients like boron, and ion gradients or currents of Ca2+, H+, and K+ are critical for pollen tube growth. However, the molecular identities of transporters mediating these fluxes are mostly unknown. As a first step to integrate transport with pollen development and function, a genome-wide analysis of transporter genes expressed in the male gametophyte at four developmental stages was conducted. About 1269 genes encoding classified transporters were collected from themore » Arabidopsis thaliana genome. Of 757 transporter genes expressed in pollen, 16% or 124 genes, including AHA6, CNGC18, TIP1.3 and CHX08, are specifically or preferentially expressed relative to sporophytic tissues. Some genes are highly expressed in microspores and bicellular pollen (COPT3, STP2, OPT9); while others are activated only in tricellular or mature pollen (STP11, LHT7). Analyses of entire gene families showed that a subset of genes, including those expressed in sporophytic tissues, were developmentally-regulated during pollen maturation. Early and late expression patterns revealed by transcriptome analysis are supported by promoter::GUS analyses of CHX genes and by other methods. Recent genetic studies based on a few transporters, including plasma membrane H+ pump AHA3, Ca2+ pump ACA9, and K+ channel SPIK, further support the expression patterns and the inferred functions revealed by our analyses. Thus, revealing the distinct expression patterns of specific transporters and unknown polytopic proteins during microgametogenesis provides new insights for strategic mutant analyses necessary to integrate the roles of transporters and potential receptors with male gametophyte development.« less

Integrating membrane transport with male gametophyte development and function through transcriptomics.

PubMed

Bock, Kevin W; Honys, David; Ward, John M; Padmanaban, Senthilkumar; Nawrocki, Eric P; Hirschi, Kendal D; Twell, David; Sze, Heven

2006-04-01

Male fertility depends on the proper development of the male gametophyte, successful pollen germination, tube growth, and delivery of the sperm cells to the ovule. Previous studies have shown that nutrients like boron, and ion gradients or currents of Ca2+, H+, and K+ are critical for pollen tube growth. However, the molecular identities of transporters mediating these fluxes are mostly unknown. As a first step to integrate transport with pollen development and function, a genome-wide analysis of transporter genes expressed in the male gametophyte at four developmental stages was conducted. Approximately 1,269 genes encoding classified transporters were collected from the Arabidopsis (Arabidopsis thaliana) genome. Of 757 transporter genes expressed in pollen, 16% or 124 genes, including AHA6, CNGC18, TIP1.3, and CHX08, are specifically or preferentially expressed relative to sporophytic tissues. Some genes are highly expressed in microspores and bicellular pollen (COPT3, STP2, OPT9), while others are activated only in tricellular or mature pollen (STP11, LHT7). Analyses of entire gene families showed that a subset of genes, including those expressed in sporophytic tissues, was developmentally regulated during pollen maturation. Early and late expression patterns revealed by transcriptome analysis are supported by promoter::beta-glucuronidase analyses of CHX genes and by other methods. Recent genetic studies based on a few transporters, including plasma membrane H+ pump AHA3, Ca2+ pump ACA9, and K+ channel SPIK, further support the expression patterns and the inferred functions revealed by our analyses. Thus, revealing the distinct expression patterns of specific transporters and unknown polytopic proteins during microgametogenesis provides new insights for strategic mutant analyses necessary to integrate the roles of transporters and potential receptors with male gametophyte development.

Integrative Clinical Genomics of Metastatic Cancer

PubMed Central

Robinson, Dan R.; Wu, Yi-Mi; Lonigro, Robert J.; Vats, Pankaj; Cobain, Erin; Everett, Jessica; Cao, Xuhong; Rabban, Erica; Kumar-Sinha, Chandan; Raymond, Victoria; Schuetze, Scott; Alva, Ajjai; Siddiqui, Javed; Chugh, Rashmi; Worden, Francis; Zalupski, Mark M.; Innis, Jeffrey; Mody, Rajen J.; Tomlins, Scott A.; Lucas, David; Baker, Laurence H.; Ramnath, Nithya; Schott, Ann F.; Hayes, Daniel F.; Vijai, Joseph; Offit, Kenneth; Stoffel, Elena M.; Roberts, J. Scott; Smith, David C.; Kunju, Lakshmi P.; Talpaz, Moshe; Cieslik, Marcin; Chinnaiyan, Arul M.

2017-01-01

SUMMARY Metastasis is the primary cause of cancer-related deaths. While The Cancer Genome Atlas (TCGA) has sequenced primary tumor types obtained from surgical resections, much less comprehensive molecular analysis is available from clinically acquired metastatic cancers. Here, we perform whole exome and transcriptome sequencing of 500 adult patients with metastatic solid tumors of diverse lineage and biopsy site. The most prevalent genes somatically altered in metastatic cancer included TP53, CDKN2A, PTEN, PIK3CA, and RB1. Putative pathogenic germline variants were present in 12.2% of cases of which 75% were related to defects in DNA repair. RNA sequencing complemented DNA sequencing for the identification of gene fusions, pathway activation, and immune profiling. Integrative sequence analysis provides a clinically relevant, multi-dimensional view of the complex molecular landscape and microenvironment of metastatic cancers. PMID:28783718

Myeloid differentiation architecture of leukocyte transcriptome dynamics in perceived social isolation

PubMed Central

Cole, Steven W.; Capitanio, John P.; Chun, Katie; Arevalo, Jesusa M. G.; Ma, Jeffrey; Cacioppo, John T.

2015-01-01

To define the cellular mechanisms of up-regulated inflammatory gene expression and down-regulated antiviral response in people experiencing perceived social isolation (loneliness), we conducted integrative analyses of leukocyte gene regulation in humans and rhesus macaques. Five longitudinal leukocyte transcriptome surveys in 141 older adults showed up-regulation of the sympathetic nervous system (SNS), monocyte population expansion, and up-regulation of the leukocyte conserved transcriptional response to adversity (CTRA). Mechanistic analyses in a macaque model of perceived social isolation confirmed CTRA activation and identified selective up-regulation of the CD14++/CD16− classical monocyte transcriptome, functional glucocorticoid desensitization, down-regulation of Type I and II interferons, and impaired response to infection by simian immunodeficiency virus (SIV). These analyses identify neuroendocrine-related alterations in myeloid cell population dynamics as a key mediator of CTRA transcriptome skewing, which may both propagate perceived social isolation and contribute to its associated health risks. PMID:26598672

Integrative biological analysis for neuropsychopharmacology.

PubMed

Emmett, Mark R; Kroes, Roger A; Moskal, Joseph R; Conrad, Charles A; Priebe, Waldemar; Laezza, Fernanda; Meyer-Baese, Anke; Nilsson, Carol L

2014-01-01

Although advances in psychotherapy have been made in recent years, drug discovery for brain diseases such as schizophrenia and mood disorders has stagnated. The need for new biomarkers and validated therapeutic targets in the field of neuropsychopharmacology is widely unmet. The brain is the most complex part of human anatomy from the standpoint of number and types of cells, their interconnections, and circuitry. To better meet patient needs, improved methods to approach brain studies by understanding functional networks that interact with the genome are being developed. The integrated biological approaches--proteomics, transcriptomics, metabolomics, and glycomics--have a strong record in several areas of biomedicine, including neurochemistry and neuro-oncology. Published applications of an integrated approach to projects of neurological, psychiatric, and pharmacological natures are still few but show promise to provide deep biological knowledge derived from cells, animal models, and clinical materials. Future studies that yield insights based on integrated analyses promise to deliver new therapeutic targets and biomarkers for personalized medicine.

Analysis of metabolomic data: tools, current strategies and future challenges for omics data integration.

PubMed

Cambiaghi, Alice; Ferrario, Manuela; Masseroli, Marco

2017-05-01

Metabolomics is a rapidly growing field consisting of the analysis of a large number of metabolites at a system scale. The two major goals of metabolomics are the identification of the metabolites characterizing each organism state and the measurement of their dynamics under different situations (e.g. pathological conditions, environmental factors). Knowledge about metabolites is crucial for the understanding of most cellular phenomena, but this information alone is not sufficient to gain a comprehensive view of all the biological processes involved. Integrated approaches combining metabolomics with transcriptomics and proteomics are thus required to obtain much deeper insights than any of these techniques alone. Although this information is available, multilevel integration of different 'omics' data is still a challenge. The handling, processing, analysis and integration of these data require specialized mathematical, statistical and bioinformatics tools, and several technical problems hampering a rapid progress in the field exist. Here, we review four main tools for number of users or provided features (MetaCoreTM, MetaboAnalyst, InCroMAP and 3Omics) out of the several available for metabolomic data analysis and integration with other 'omics' data, highlighting their strong and weak aspects; a number of related issues affecting data analysis and integration are also identified and discussed. Overall, we provide an objective description of how some of the main currently available software packages work, which may help the experimental practitioner in the choice of a robust pipeline for metabolomic data analysis and integration. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Characterization and Comparative Analysis of the Milk Transcriptome in Two Dairy Sheep Breeds using RNA Sequencing.

PubMed

Suárez-Vega, Aroa; Gutiérrez-Gil, Beatriz; Klopp, Christophe; Robert-Granie, Christèle; Tosser-Klopp, Gwenola; Arranz, Juan José

2015-12-18

This study presents a dynamic characterization of the sheep milk transcriptome aiming at achieving a better understanding of the sheep lactating mammary gland. Transcriptome sequencing (RNA-seq) was performed on total RNA extracted from milk somatic cells from ewes on days 10, 50, 120 and 150 after lambing. The experiment was performed in Spanish Churra and Assaf breeds, which differ in their milk production traits. Nearly 67% of the annotated genes in the reference genome (Oar_v3.1) were expressed in ovine milk somatic cells. For the two breeds and across the four lactation stages studied, the most highly expressed genes encoded caseins and whey proteins. We detected 573 differentially expressed genes (DEGs) across lactation points, with the largest differences being found, between day 10 and day 150. Upregulated GO terms at late lactation stages were linked mainly to developmental processes linked to extracellular matrix remodeling. A total of 256 annotated DEGs were detected in the Assaf and Churra comparison. Some genes selectively upregulated in the Churra breed grouped under the endopeptidase and channel activity GO terms. These genes could be related to the higher cheese yield of this breed. Overall, this study provides the first integrated overview on sheep milk gene expression.

Comparative Transcriptomics Among Four White Pine Species.

PubMed

Baker, Ethan A G; Wegrzyn, Jill L; Sezen, Uzay U; Falk, Taylor; Maloney, Patricia E; Vogler, Detlev R; Delfino-Mix, Annette; Jensen, Camille; Mitton, Jeffry; Wright, Jessica; Knaus, Brian; Rai, Hardeep; Cronn, Richard; Gonzalez-Ibeas, Daniel; Vasquez-Gross, Hans A; Famula, Randi A; Liu, Jun-Jun; Kueppers, Lara M; Neale, David B

2018-05-04

Conifers are the dominant plant species throughout the high latitude boreal forests as well as some lower latitude temperate forests of North America, Europe, and Asia. As such, they play an integral economic and ecological role across much of the world. This study focused on the characterization of needle transcriptomes from four ecologically important and understudied North American white pines within the Pinus subgenus Strobus The populations of many Strobus species are challenged by native and introduced pathogens, native insects, and abiotic factors. RNA from the needles of western white pine ( Pinus monticola ), limber pine ( Pinus flexilis ), whitebark pine ( Pinus albicaulis) , and sugar pine ( Pinus lambertiana ) was sampled, Illumina short read sequenced, and de novo assembled. The assembled transcripts and their subsequent structural and functional annotations were processed through custom pipelines to contend with the challenges of non-model organism transcriptome validation. Orthologous gene family analysis of over 58,000 translated transcripts, implemented through Tribe-MCL, estimated the shared and unique gene space among the four species. This revealed 2025 conserved gene families, of which 408 were aligned to estimate levels of divergence and reveal patterns of selection. Specific candidate genes previously associated with drought tolerance and white pine blister rust resistance in conifers were investigated. Copyright © 2018 Baker et al.

Suboptimal evolutionary novel environments promote singular altered gravity responses of transcriptome during Drosophila metamorphosis

PubMed Central

2013-01-01

Background Previous experiments have shown that the reduced gravity aboard the International Space Station (ISS) causes important alterations in Drosophila gene expression. These changes were shown to be intimately linked to environmental space-flight related constraints. Results Here, we use an array of different techniques for ground-based simulation of microgravity effects to assess the effect of suboptimal environmental conditions on the gene expression of Drosophila in reduced gravity. A global and integrative analysis, using “gene expression dynamics inspector” (GEDI) self-organizing maps, reveals different degrees in the responses of the transcriptome when using different environmental conditions or microgravity/hypergravity simulation devices. Although the genes that are affected are different in each simulation technique, we find that the same gene ontology groups, including at least one large multigene family related with behavior, stress response or organogenesis, are over represented in each case. Conclusions These results suggest that the transcriptome as a whole can be finely tuned to gravity force. In optimum environmental conditions, the alteration of gravity has only mild effects on gene expression but when environmental conditions are far from optimal, the gene expression must be tuned greatly and effects become more robust, probably linked to the lack of experience of organisms exposed to evolutionary novel environments such as a gravitational free one. PMID:23806134

Characterization and Comparative Analysis of the Milk Transcriptome in Two Dairy Sheep Breeds using RNA Sequencing

PubMed Central

Suárez-Vega, Aroa; Gutiérrez-Gil, Beatriz; Klopp, Christophe; Robert-Granie, Christèle; Tosser-Klopp, Gwenola; Arranz, Juan José

2015-01-01

This study presents a dynamic characterization of the sheep milk transcriptome aiming at achieving a better understanding of the sheep lactating mammary gland. Transcriptome sequencing (RNA-seq) was performed on total RNA extracted from milk somatic cells from ewes on days 10, 50, 120 and 150 after lambing. The experiment was performed in Spanish Churra and Assaf breeds, which differ in their milk production traits. Nearly 67% of the annotated genes in the reference genome (Oar_v3.1) were expressed in ovine milk somatic cells. For the two breeds and across the four lactation stages studied, the most highly expressed genes encoded caseins and whey proteins. We detected 573 differentially expressed genes (DEGs) across lactation points, with the largest differences being found, between day 10 and day 150. Upregulated GO terms at late lactation stages were linked mainly to developmental processes linked to extracellular matrix remodeling. A total of 256 annotated DEGs were detected in the Assaf and Churra comparison. Some genes selectively upregulated in the Churra breed grouped under the endopeptidase and channel activity GO terms. These genes could be related to the higher cheese yield of this breed. Overall, this study provides the first integrated overview on sheep milk gene expression. PMID:26677795

Integrating Omics and Alternative Splicing Reveals Insights into Grape Response to High Temperature1[OPEN

PubMed Central

Jiang, Jianfu; Liu, Xinna; Liu, Guotian; Li, Shaohua

2017-01-01

Heat stress is one of the primary abiotic stresses that limit crop production. Grape (Vitis vinifera) is a cultivated fruit with high economic value throughout the world, with its growth and development often influenced by high temperature. Alternative splicing (AS) is a widespread phenomenon increasing transcriptome and proteome diversity. We conducted high-temperature treatments (35°C, 40°C, and 45°C) on grapevines and assessed transcriptomic (especially AS) and proteomic changes in leaves. We found that nearly 70% of the genes were alternatively spliced under high temperature. Intron retention (IR), exon skipping, and alternative donor/acceptor sites were markedly induced under different high temperatures. Among all differential AS events, IR was the most abundant up- and down-regulated event. Moreover, the occurrence frequency of IR events at 40°C and 45°C was far higher than at 35°C. These results indicated that AS, especially IR, is an important posttranscriptional regulatory event during grape leaf responses to high temperature. Proteomic analysis showed that protein levels of the RNA-binding proteins SR45, SR30, and SR34 and the nuclear ribonucleic protein U1A gradually rose as ambient temperature increased, which revealed a reason why AS events occurred more frequently under high temperature. After integrating transcriptomic and proteomic data, we found that heat shock proteins and some important transcription factors such as MULTIPROTEIN BRIDGING FACTOR1c and HEAT SHOCK TRANSCRIPTION FACTOR A2 were involved mainly in heat tolerance in grape through up-regulating transcriptional (especially modulated by AS) and translational levels. To our knowledge, these results provide the first evidence for grape leaf responses to high temperature at simultaneous transcriptional, posttranscriptional, and translational levels. PMID:28049741

Integrating Omics and Alternative Splicing Reveals Insights into Grape Response to High Temperature.

PubMed

Jiang, Jianfu; Liu, Xinna; Liu, Chonghuai; Liu, Guotian; Li, Shaohua; Wang, Lijun

2017-02-01

Heat stress is one of the primary abiotic stresses that limit crop production. Grape (Vitis vinifera) is a cultivated fruit with high economic value throughout the world, with its growth and development often influenced by high temperature. Alternative splicing (AS) is a widespread phenomenon increasing transcriptome and proteome diversity. We conducted high-temperature treatments (35°C, 40°C, and 45°C) on grapevines and assessed transcriptomic (especially AS) and proteomic changes in leaves. We found that nearly 70% of the genes were alternatively spliced under high temperature. Intron retention (IR), exon skipping, and alternative donor/acceptor sites were markedly induced under different high temperatures. Among all differential AS events, IR was the most abundant up- and down-regulated event. Moreover, the occurrence frequency of IR events at 40°C and 45°C was far higher than at 35°C. These results indicated that AS, especially IR, is an important posttranscriptional regulatory event during grape leaf responses to high temperature. Proteomic analysis showed that protein levels of the RNA-binding proteins SR45, SR30, and SR34 and the nuclear ribonucleic protein U1A gradually rose as ambient temperature increased, which revealed a reason why AS events occurred more frequently under high temperature. After integrating transcriptomic and proteomic data, we found that heat shock proteins and some important transcription factors such as MULTIPROTEIN BRIDGING FACTOR1c and HEAT SHOCK TRANSCRIPTION FACTOR A2 were involved mainly in heat tolerance in grape through up-regulating transcriptional (especially modulated by AS) and translational levels. To our knowledge, these results provide the first evidence for grape leaf responses to high temperature at simultaneous transcriptional, posttranscriptional, and translational levels. © 2017 American Society of Plant Biologists. All Rights Reserved.

The molecular basis of breast cancer pathological phenotypes.

PubMed

Heng, Yujing J; Lester, Susan C; Tse, Gary Mk; Factor, Rachel E; Allison, Kimberly H; Collins, Laura C; Chen, Yunn-Yi; Jensen, Kristin C; Johnson, Nicole B; Jeong, Jong Cheol; Punjabi, Rahi; Shin, Sandra J; Singh, Kamaljeet; Krings, Gregor; Eberhard, David A; Tan, Puay Hoon; Korski, Konstanty; Waldman, Frederic M; Gutman, David A; Sanders, Melinda; Reis-Filho, Jorge S; Flanagan, Sydney R; Gendoo, Deena Ma; Chen, Gregory M; Haibe-Kains, Benjamin; Ciriello, Giovanni; Hoadley, Katherine A; Perou, Charles M; Beck, Andrew H

2017-02-01

The histopathological evaluation of morphological features in breast tumours provides prognostic information to guide therapy. Adjunct molecular analyses provide further diagnostic, prognostic and predictive information. However, there is limited knowledge of the molecular basis of morphological phenotypes in invasive breast cancer. This study integrated genomic, transcriptomic and protein data to provide a comprehensive molecular profiling of morphological features in breast cancer. Fifteen pathologists assessed 850 invasive breast cancer cases from The Cancer Genome Atlas (TCGA). Morphological features were significantly associated with genomic alteration, DNA methylation subtype, PAM50 and microRNA subtypes, proliferation scores, gene expression and/or reverse-phase protein assay subtype. Marked nuclear pleomorphism, necrosis, inflammation and a high mitotic count were associated with the basal-like subtype, and had a similar molecular basis. Omics-based signatures were constructed to predict morphological features. The association of morphology transcriptome signatures with overall survival in oestrogen receptor (ER)-positive and ER-negative breast cancer was first assessed by use of the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) dataset; signatures that remained prognostic in the METABRIC multivariate analysis were further evaluated in five additional datasets. The transcriptomic signature of poorly differentiated epithelial tubules was prognostic in ER-positive breast cancer. No signature was prognostic in ER-negative breast cancer. This study provided new insights into the molecular basis of breast cancer morphological phenotypes. The integration of morphological with molecular data has the potential to refine breast cancer classification, predict response to therapy, enhance our understanding of breast cancer biology, and improve clinical management. This work is publicly accessible at www.dx.ai/tcga_breast. Copyright © 2016 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd. Copyright © 2016 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Integrated Left Ventricular Global Transcriptome and Proteome Profiling in Human End-Stage Dilated Cardiomyopathy.

PubMed

Colak, Dilek; Alaiya, Ayodele A; Kaya, Namik; Muiya, Nzioka P; AlHarazi, Olfat; Shinwari, Zakia; Andres, Editha; Dzimiri, Nduna

2016-01-01

The disease pathways leading to idiopathic dilated cardiomyopathy (DCM) are still elusive. The present study investigated integrated global transcriptional and translational changes in human DCM for disease biomarker discovery. We used identical myocardial tissues from five DCM hearts compared to five non-failing (NF) donor hearts for both transcriptome profiling using the ABI high-density oligonucleotide microarrays and proteome expression with One-Dimensional Nano Acquity liquid chromatography coupled with tandem mass spectrometry on the Synapt G2 system. We identified 1262 differentially expressed genes (DEGs) and 269 proteins (DEPs) between DCM cases and healthy controls. Among the most significantly upregulated (>5-fold) proteins were GRK5, APOA2, IGHG3, ANXA6, HSP90AA1, and ATP5C1 (p< 0.01). On the other hand, the most significantly downregulated proteins were GSTM5, COX17, CAV1 and ANXA3. At least ten entities were concomitantly upregulated on the two analysis platforms: GOT1, ALDH4A1, PDHB, BDH1, SLC2A11, HSP90AA1, HSP90AB1, H2AFV, HSPA5 and NDUFV1. Gene ontology analyses of DEGs and DEPs revealed significant overlap with enrichment of genes/proteins related to metabolic process, biosynthetic process, cellular component organization, oxidative phosphorylation, alterations in glycolysis and ATP synthesis, Alzheimer's disease, chemokine-mediated inflammation and cytokine signalling pathways. The concomitant use of transcriptome and proteome expression to evaluate global changes in DCM has led to the identification of sixteen commonly altered entities as well as novel genes, proteins and pathways whose cardiac functions have yet to be deciphered. This data should contribute towards better management of the disease.

Integrating single-cell transcriptomic data across different conditions, technologies, and species.

PubMed

Butler, Andrew; Hoffman, Paul; Smibert, Peter; Papalexi, Efthymia; Satija, Rahul

2018-06-01

Computational single-cell RNA-seq (scRNA-seq) methods have been successfully applied to experiments representing a single condition, technology, or species to discover and define cellular phenotypes. However, identifying subpopulations of cells that are present across multiple data sets remains challenging. Here, we introduce an analytical strategy for integrating scRNA-seq data sets based on common sources of variation, enabling the identification of shared populations across data sets and downstream comparative analysis. We apply this approach, implemented in our R toolkit Seurat (http://satijalab.org/seurat/), to align scRNA-seq data sets of peripheral blood mononuclear cells under resting and stimulated conditions, hematopoietic progenitors sequenced using two profiling technologies, and pancreatic cell 'atlases' generated from human and mouse islets. In each case, we learn distinct or transitional cell states jointly across data sets, while boosting statistical power through integrated analysis. Our approach facilitates general comparisons of scRNA-seq data sets, potentially deepening our understanding of how distinct cell states respond to perturbation, disease, and evolution.

On the way toward systems biology of Aspergillus fumigatus infection.

PubMed

Albrecht, Daniela; Kniemeyer, Olaf; Mech, Franziska; Gunzer, Matthias; Brakhage, Axel; Guthke, Reinhard

2011-06-01

Pathogenicity of Aspergillus fumigatus is multifactorial. Thus, global studies are essential for the understanding of the infection process. Therefore, a data warehouse was established where genome sequence, transcriptome and proteome data are stored. These data are analyzed for the elucidation of virulence determinants. The data analysis workflow starts with pre-processing including imputing of missing values and normalization. Last step is the identification of differentially expressed genes/proteins as interesting candidates for further analysis, in particular for functional categorization and correlation studies. Sequence data and other prior knowledge extracted from databases are integrated to support the inference of gene regulatory networks associated with pathogenicity. This knowledge-assisted data analysis aims at establishing mathematical models with predictive strength to assist further experimental work. Recently, first steps were done to extend the integrative data analysis and computational modeling by evaluating spatio-temporal data (movies) that monitor interactions of A. fumigatus morphotypes (e.g. conidia) with host immune cells. Copyright © 2011 Elsevier GmbH. All rights reserved.

Insights into transcriptomes of Big and Low sagebrush

Treesearch

Mark D. Huynh; Justin T. Page; Bryce A. Richardson; Joshua A. Udall

2015-01-01

We report the sequencing and assembly of three transcriptomes from Big (Artemisia tridentatassp. wyomingensis and A. tridentatassp. tridentata) and Low (A. arbuscula ssp. arbuscula) sagebrush. The sequence reads are available in the Sequence Read Archive of NCBI. We demonstrate the utilities of these transcriptomes for gene discovery and phylogenomic analysis. An...

Data integration aids understanding of butterfly-host plant networks

NASA Astrophysics Data System (ADS)

Muto-Fujita, Ai; Takemoto, Kazuhiro; Kanaya, Shigehiko; Nakazato, Takeru; Tokimatsu, Toshiaki; Matsumoto, Natsushi; Kono, Mayo; Chubachi, Yuko; Ozaki, Katsuhisa; Kotera, Masaaki

2017-03-01

Although host-plant selection is a central topic in ecology, its general underpinnings are poorly understood. Here, we performed a case study focusing on the publicly available data on Japanese butterflies. A combined statistical analysis of plant-herbivore relationships and taxonomy revealed that some butterfly subfamilies in different families feed on the same plant families, and the occurrence of this phenomenon more than just by chance, thus indicating the independent acquisition of adaptive phenotypes to the same hosts. We consequently integrated plant-herbivore and plant-compound relationship data and conducted a statistical analysis to identify compounds unique to host plants of specific butterfly families. Some of the identified plant compounds are known to attract certain butterfly groups while repelling others. The additional incorporation of insect-compound relationship data revealed potential metabolic processes that are related to host plant selection. Our results demonstrate that data integration enables the computational detection of compounds putatively involved in particular interspecies interactions and that further data enrichment and integration of genomic and transcriptomic data facilitates the unveiling of the molecular mechanisms involved in host plant selection.

Data integration aids understanding of butterfly–host plant networks

PubMed Central

Muto-Fujita, Ai; Takemoto, Kazuhiro; Kanaya, Shigehiko; Nakazato, Takeru; Tokimatsu, Toshiaki; Matsumoto, Natsushi; Kono, Mayo; Chubachi, Yuko; Ozaki, Katsuhisa; Kotera, Masaaki

2017-01-01

Although host-plant selection is a central topic in ecology, its general underpinnings are poorly understood. Here, we performed a case study focusing on the publicly available data on Japanese butterflies. A combined statistical analysis of plant–herbivore relationships and taxonomy revealed that some butterfly subfamilies in different families feed on the same plant families, and the occurrence of this phenomenon more than just by chance, thus indicating the independent acquisition of adaptive phenotypes to the same hosts. We consequently integrated plant–herbivore and plant–compound relationship data and conducted a statistical analysis to identify compounds unique to host plants of specific butterfly families. Some of the identified plant compounds are known to attract certain butterfly groups while repelling others. The additional incorporation of insect–compound relationship data revealed potential metabolic processes that are related to host plant selection. Our results demonstrate that data integration enables the computational detection of compounds putatively involved in particular interspecies interactions and that further data enrichment and integration of genomic and transcriptomic data facilitates the unveiling of the molecular mechanisms involved in host plant selection. PMID:28262809

Transcriptomics and proteomics show that selenium affects inflammation, cytoskeleton, and cancer pathways in human rectal biopsies.

PubMed

Méplan, Catherine; Johnson, Ian T; Polley, Abigael C J; Cockell, Simon; Bradburn, David M; Commane, Daniel M; Arasaradnam, Ramesh P; Mulholland, Francis; Zupanic, Anze; Mathers, John C; Hesketh, John

2016-08-01

Epidemiologic studies highlight the potential role of dietary selenium (Se) in colorectal cancer prevention. Our goal was to elucidate whether expression of factors crucial for colorectal homoeostasis is affected by physiologic differences in Se status. Using transcriptomics and proteomics followed by pathway analysis, we identified pathways affected by Se status in rectal biopsies from 22 healthy adults, including 11 controls with optimal status (mean plasma Se = 1.43 μM) and 11 subjects with suboptimal status (mean plasma Se = 0.86 μM). We observed that 254 genes and 26 proteins implicated in cancer (80%), immune function and inflammatory response (40%), cell growth and proliferation (70%), cellular movement, and cell death (50%) were differentially expressed between the 2 groups. Expression of 69 genes, including selenoproteins W1 and K, which are genes involved in cytoskeleton remodelling and transcription factor NFκB signaling, correlated significantly with Se status. Integrating proteomics and transcriptomics datasets revealed reduced inflammatory and immune responses and cytoskeleton remodelling in the suboptimal Se status group. This is the first study combining omics technologies to describe the impact of differences in Se status on colorectal expression patterns, revealing that suboptimal Se status could alter inflammatory signaling and cytoskeleton in human rectal mucosa and so influence cancer risk.-Méplan, C., Johnson, I. T., Polley, A. C. J., Cockell, S., Bradburn, D. M., Commane, D. M., Arasaradnam, R. P., Mulholland, F., Zupanic, A., Mathers, J. C., Hesketh, J. Transcriptomics and proteomics show that selenium affects inflammation, cytoskeleton, and cancer pathways in human rectal biopsies. © The Author(s).

Proteomics and transcriptomics analyses of Arabidopsis floral buds uncover important functions of ARABIDOPSIS SKP1-LIKE1

DOE PAGES

Lu, Dihong; Ni, Weimin; Stanley, Bruce A.; ...

2016-03-03

The ARABIDOPSIS SKP1-LIKE1 (ASK1) protein functions as a subunit of SKP1-CUL1-F-box (SCF) E3 ubiquitin ligases. Previous genetic studies showed that ASK1 plays important roles in Arabidopsis flower development and male meiosis. However, the molecular impact of ASK1-containing SCF E3 ubiquitin ligases (ASK1-E3s) on the floral proteome and transcriptome is unknown. Here we identified proteins that are potentially regulated by ASK1-E3s by comparing floral bud proteomes of wild-type and the ask1 mutant plants. More than 200 proteins were detected in the ask1 mutant but not in wild-type and >300 were detected at higher levels in the ask1 mutant than in wild-type,more » but their RNA levels were not significantly different between wild-type and ask1 floral buds as shown by transcriptomics analysis, suggesting that they are likely regulated at the protein level by ASK1-E3s. Integrated analyses of floral proteomics and transcriptomics of ask1 and wild-type uncovered several potential aspects of ASK1-E3 functions, including regulation of transcription regulators, kinases, peptidases, and ribosomal proteins, with implications on possible mechanisms of ASK1-E3 functions in floral development. In conclusion, our results suggested that ASK1-E3s play important roles in Arabidopsis protein degradation during flower development. This study opens up new possibilities for further functional studies of these candidate E3 substrates.« less

Proteomics and transcriptomics analyses of Arabidopsis floral buds uncover important functions of ARABIDOPSIS SKP1-LIKE1

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lu, Dihong; Ni, Weimin; Stanley, Bruce A.

The ARABIDOPSIS SKP1-LIKE1 (ASK1) protein functions as a subunit of SKP1-CUL1-F-box (SCF) E3 ubiquitin ligases. Previous genetic studies showed that ASK1 plays important roles in Arabidopsis flower development and male meiosis. However, the molecular impact of ASK1-containing SCF E3 ubiquitin ligases (ASK1-E3s) on the floral proteome and transcriptome is unknown. Here we identified proteins that are potentially regulated by ASK1-E3s by comparing floral bud proteomes of wild-type and the ask1 mutant plants. More than 200 proteins were detected in the ask1 mutant but not in wild-type and >300 were detected at higher levels in the ask1 mutant than in wild-type,more » but their RNA levels were not significantly different between wild-type and ask1 floral buds as shown by transcriptomics analysis, suggesting that they are likely regulated at the protein level by ASK1-E3s. Integrated analyses of floral proteomics and transcriptomics of ask1 and wild-type uncovered several potential aspects of ASK1-E3 functions, including regulation of transcription regulators, kinases, peptidases, and ribosomal proteins, with implications on possible mechanisms of ASK1-E3 functions in floral development. In conclusion, our results suggested that ASK1-E3s play important roles in Arabidopsis protein degradation during flower development. This study opens up new possibilities for further functional studies of these candidate E3 substrates.« less

Using next generation transcriptome sequencing to predict an ectomycorrhizal metablome.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Larsen, P. E.; Sreedasyam, A.; Trivedi, G

Mycorrhizae, symbiotic interactions between soil fungi and tree roots, are ubiquitous in terrestrial ecosystems. The fungi contribute phosphorous, nitrogen and mobilized nutrients from organic matter in the soil and in return the fungus receives photosynthetically-derived carbohydrates. This union of plant and fungal metabolisms is the mycorrhizal metabolome. Understanding this symbiotic relationship at a molecular level provides important contributions to the understanding of forest ecosystems and global carbon cycling. We generated next generation short-read transcriptomic sequencing data from fully-formed ectomycorrhizae between Laccaria bicolor and aspen (Populus tremuloides) roots. The transcriptomic data was used to identify statistically significantly expressed gene models usingmore » a bootstrap-style approach, and these expressed genes were mapped to specific metabolic pathways. Integration of expressed genes that code for metabolic enzymes and the set of expressed membrane transporters generates a predictive model of the ectomycorrhizal metabolome. The generated model of mycorrhizal metabolome predicts that the specific compounds glycine, glutamate, and allantoin are synthesized by L. bicolor and that these compounds or their metabolites may be used for the benefit of aspen in exchange for the photosynthetically-derived sugars fructose and glucose. The analysis illustrates an approach to generate testable biological hypotheses to investigate the complex molecular interactions that drive ectomycorrhizal symbiosis. These models are consistent with experimental environmental data and provide insight into the molecular exchange processes for organisms in this complex ecosystem. The method used here for predicting metabolomic models of mycorrhizal systems from deep RNA sequencing data can be generalized and is broadly applicable to transcriptomic data derived from complex systems.« less

Separation and parallel sequencing of the genomes and transcriptomes of single cells using G&T-seq.

PubMed

Macaulay, Iain C; Teng, Mabel J; Haerty, Wilfried; Kumar, Parveen; Ponting, Chris P; Voet, Thierry

2016-11-01

Parallel sequencing of a single cell's genome and transcriptome provides a powerful tool for dissecting genetic variation and its relationship with gene expression. Here we present a detailed protocol for G&T-seq, a method for separation and parallel sequencing of genomic DNA and full-length polyA(+) mRNA from single cells. We provide step-by-step instructions for the isolation and lysis of single cells; the physical separation of polyA(+) mRNA from genomic DNA using a modified oligo-dT bead capture and the respective whole-transcriptome and whole-genome amplifications; and library preparation and sequence analyses of these amplification products. The method allows the detection of thousands of transcripts in parallel with the genetic variants captured by the DNA-seq data from the same single cell. G&T-seq differs from other currently available methods for parallel DNA and RNA sequencing from single cells, as it involves physical separation of the DNA and RNA and does not require bespoke microfluidics platforms. The process can be implemented manually or through automation. When performed manually, paired genome and transcriptome sequencing libraries from eight single cells can be produced in ∼3 d by researchers experienced in molecular laboratory work. For users with experience in the programming and operation of liquid-handling robots, paired DNA and RNA libraries from 96 single cells can be produced in the same time frame. Sequence analysis and integration of single-cell G&T-seq DNA and RNA data requires a high level of bioinformatics expertise and familiarity with a wide range of informatics tools.

Transcriptome Analysis of the Emerald Ash Borer (EAB), Agrilus planipennis: De Novo Assembly, Functional Annotation and Comparative Analysis.

PubMed

Duan, Jun; Ladd, Tim; Doucet, Daniel; Cusson, Michel; vanFrankenhuyzen, Kees; Mittapalli, Omprakash; Krell, Peter J; Quan, Guoxing

2015-01-01

The Emerald ash borer (EAB), Agrilus planipennis, is an invasive phloem-feeding insect pest of ash trees. Since its initial discovery near the Detroit, US- Windsor, Canada area in 2002, the spread of EAB has had strong negative economic, social and environmental impacts in both countries. Several transcriptomes from specific tissues including midgut, fat body and antenna have recently been generated. However, the relatively low sequence depth, gene coverage and completeness limited the usefulness of these EAB databases. High-throughput deep RNA-Sequencing (RNA-Seq) was used to obtain 473.9 million pairs of 100 bp length paired-end reads from various life stages and tissues. These reads were assembled into 88,907 contigs using the Trinity strategy and integrated into 38,160 unigenes after redundant sequences were removed. We annotated 11,229 unigenes by searching against the public nr, Swiss-Prot and COG. The EAB transcriptome assembly was compared with 13 other sequenced insect species, resulting in the prediction of 536 unigenes that are Coleoptera-specific. Differential gene expression revealed that 290 unigenes are expressed during larval molting and 3,911 unigenes during metamorphosis from larvae to pupae, respectively (FDR< 0.01 and log2 FC>2). In addition, 1,167 differentially expressed unigenes were identified from larval and adult midguts, 435 unigenes were up-regulated in larval midgut and 732 unigenes were up-regulated in adult midgut. Most of the genes involved in RNA interference (RNAi) pathways were identified, which implies the existence of a system RNAi in EAB. This study provides one of the most fundamental and comprehensive transcriptome resources available for EAB to date. Identification of the tissue- stage- or species- specific unigenes will benefit the further study of gene functions during growth and metamorphosis processes in EAB and other pest insects.

Transcriptome Analysis of the Emerald Ash Borer (EAB), Agrilus planipennis: De Novo Assembly, Functional Annotation and Comparative Analysis

PubMed Central

Duan, Jun; Ladd, Tim; Doucet, Daniel; Cusson, Michel; vanFrankenhuyzen, Kees; Mittapalli, Omprakash; Krell, Peter J.; Quan, Guoxing

2015-01-01

Background The Emerald ash borer (EAB), Agrilus planipennis, is an invasive phloem-feeding insect pest of ash trees. Since its initial discovery near the Detroit, US- Windsor, Canada area in 2002, the spread of EAB has had strong negative economic, social and environmental impacts in both countries. Several transcriptomes from specific tissues including midgut, fat body and antenna have recently been generated. However, the relatively low sequence depth, gene coverage and completeness limited the usefulness of these EAB databases. Methodology and Principal Findings High-throughput deep RNA-Sequencing (RNA-Seq) was used to obtain 473.9 million pairs of 100 bp length paired-end reads from various life stages and tissues. These reads were assembled into 88,907 contigs using the Trinity strategy and integrated into 38,160 unigenes after redundant sequences were removed. We annotated 11,229 unigenes by searching against the public nr, Swiss-Prot and COG. The EAB transcriptome assembly was compared with 13 other sequenced insect species, resulting in the prediction of 536 unigenes that are Coleoptera-specific. Differential gene expression revealed that 290 unigenes are expressed during larval molting and 3,911 unigenes during metamorphosis from larvae to pupae, respectively (FDR< 0.01 and log2 FC>2). In addition, 1,167 differentially expressed unigenes were identified from larval and adult midguts, 435 unigenes were up-regulated in larval midgut and 732 unigenes were up-regulated in adult midgut. Most of the genes involved in RNA interference (RNAi) pathways were identified, which implies the existence of a system RNAi in EAB. Conclusions and Significance This study provides one of the most fundamental and comprehensive transcriptome resources available for EAB to date. Identification of the tissue- stage- or species- specific unigenes will benefit the further study of gene functions during growth and metamorphosis processes in EAB and other pest insects. PMID:26244979

Scanning of Transposable Elements and Analyzing Expression of Transposase Genes of Sweet Potato [Ipomoea batatas

PubMed Central

Tao, Xiang; Lai, Xian-Jun; Zhang, Yi-Zheng; Tan, Xue-Mei; Wang, Haiyan

2014-01-01

Background Transposable elements (TEs) are the most abundant genomic components in eukaryotes and affect the genome by their replications and movements to generate genetic plasticity. Sweet potato performs asexual reproduction generally and the TEs may be an important genetic factor for genome reorganization. Complete identification of TEs is essential for the study of genome evolution. However, the TEs of sweet potato are still poorly understood because of its complex hexaploid genome and difficulty in genome sequencing. The recent availability of the sweet potato transcriptome databases provides an opportunity for discovering and characterizing the expressed TEs. Methodology/Principal Findings We first established the integrated-transcriptome database by de novo assembling four published sweet potato transcriptome databases from three cultivars in China. Using sequence-similarity search and analysis, a total of 1,405 TEs including 883 retrotransposons and 522 DNA transposons were predicted and categorized. Depending on mapping sets of RNA-Seq raw short reads to the predicted TEs, we compared the quantities, classifications and expression activities of TEs inter- and intra-cultivars. Moreover, the differential expressions of TEs in seven tissues of Xushu 18 cultivar were analyzed by using Illumina digital gene expression (DGE) tag profiling. It was found that 417 TEs were expressed in one or more tissues and 107 in all seven tissues. Furthermore, the copy number of 11 transposase genes was determined to be 1–3 copies in the genome of sweet potato by Real-time PCR-based absolute quantification. Conclusions/Significance Our result provides a new method for TE searching on species with transcriptome sequences while lacking genome information. The searching, identification and expression analysis of TEs will provide useful TE information in sweet potato, which are valuable for the further studies of TE-mediated gene mutation and optimization in asexual reproduction. It contributes to elucidating the roles of TEs in genome evolution. PMID:24608103

Transcriptome analysis in non-model species: a new method for the analysis of heterologous hybridization on microarrays

PubMed Central

2010-01-01

Background Recent developments in high-throughput methods of analyzing transcriptomic profiles are promising for many areas of biology, including ecophysiology. However, although commercial microarrays are available for most common laboratory models, transcriptome analysis in non-traditional model species still remains a challenge. Indeed, the signal resulting from heterologous hybridization is low and difficult to interpret because of the weak complementarity between probe and target sequences, especially when no microarray dedicated to a genetically close species is available. Results We show here that transcriptome analysis in a species genetically distant from laboratory models is made possible by using MAXRS, a new method of analyzing heterologous hybridization on microarrays. This method takes advantage of the design of several commercial microarrays, with different probes targeting the same transcript. To illustrate and test this method, we analyzed the transcriptome of king penguin pectoralis muscle hybridized to Affymetrix chicken microarrays, two organisms separated by an evolutionary distance of approximately 100 million years. The differential gene expression observed between different physiological situations computed by MAXRS was confirmed by real-time PCR on 10 genes out of 11 tested. Conclusions MAXRS appears to be an appropriate method for gene expression analysis under heterologous hybridization conditions. PMID:20509979

Single-cell analysis of the transcriptome and its application in the characterization of stem cells and early embryos.

PubMed

Liu, Na; Liu, Lin; Pan, Xinghua

2014-07-01

Cellular heterogeneity within a cell population is a common phenomenon in multicellular organisms, tissues, cultured cells, and even FACS-sorted subpopulations. Important information may be masked if the cells are studied as a mass. Transcriptome profiling is a parameter that has been intensively studied, and relatively easier to address than protein composition. To understand the basis and importance of heterogeneity and stochastic aspects of the cell function and its mechanisms, it is essential to examine transcriptomes of a panel of single cells. High-throughput technologies, starting from microarrays and now RNA-seq, provide a full view of the expression of transcriptomes but are limited by the amount of RNA for analysis. Recently, several new approaches for amplification and sequencing the transcriptome of single cells or a limited low number of cells have been developed and applied. In this review, we summarize these major strategies, such as PCR-based methods, IVT-based methods, phi29-DNA polymerase-based methods, and several other methods, including their principles, characteristics, advantages, and limitations, with representative applications in cancer stem cells, early development, and embryonic stem cells. The prospects for development of future technology and application of transcriptome analysis in a single cell are also discussed.

Integrative transcriptome, proteome, phosphoproteome and genetic mapping reveals new aspects in a fiberless mutant of cotton

PubMed Central

Ma, Qi-Feng; Wu, Chun-Hui; Wu, Man; Pei, Wen-Feng; Li, Xing-Li; Wang, Wen-Kui; Zhang, Jinfa; Yu, Ji-Wen; Yu, Shu-Xun

2016-01-01

To investigate the molecular mechanisms of fiber initiation in cotton (Gossypium spp.), an integrated approach combining transcriptome, iTRAQ-based proteome and genetic mapping was taken to compare the ovules of the Xuzhou 142 wild type (WT) with its fuzzless-lintless (fl) mutant at −3 and 0 day post-anthesis. A total of 1,953 mRNAs, 187 proteins, and 131 phosphoproteins were differentially expressed (DE) between WT and fl, and the levels of transcripts and their encoded proteins and phosphoproteins were highly congruent. A functional analysis suggested that the abundance of proteins were mainly involved in amino sugar, nucleotide sugar and fatty acid metabolism, one carbon pool for folate metabolism and flavonoid biosynthesis. qRT-PCR, Western blotting, and enzymatic assays were performed to confirm the regulation of these transcripts and proteins. A molecular mapping located the lintless gene li3 in the fl mutant on chromosome 26 for the first time. A further in-silico physical mapping of DE genes with sequence variations between fl and WT identified one and four candidate genes in the li3 and n2 regions, respectively. Taken together, the transcript abundance, phosphorylation status of proteins at the fiber initiation stage and candidate genes have provided insights into regulatory processes underlying cotton fiber initiation. PMID:27075604

Fish gut-liver immunity during homeostasis or inflammation revealed by integrative transcriptome and proteome studies

NASA Astrophysics Data System (ADS)

Wu, Nan; Song, Yu-Long; Wang, Bei; Zhang, Xiang-Yang; Zhang, Xu-Jie; Wang, Ya-Li; Cheng, Ying-Yin; Chen, Dan-Dan; Xia, Xiao-Qin; Lu, Yi-Shan; Zhang, Yong-An

2016-11-01

The gut-associated lymphoid tissue, connected with liver via bile and blood, constructs a local immune environment of both defense and tolerance. The gut-liver immunity has been well-studied in mammals, yet in fish remains largely unknown, even though enteritis as well as liver and gallbladder syndrome emerged as a limitation in aquaculture. In this study, we performed integrative bioinformatic analysis for both transcriptomic (gut and liver) and proteomic (intestinal mucus and bile) data, in both healthy and infected tilapias. We found more categories of immune transcripts in gut than liver, as well as more adaptive immune in gut meanwhile more innate in liver. Interestingly reduced differential immune transcripts between gut and liver upon inflammation were also revealed. In addition, more immune proteins in bile than intestinal mucus were identified. And bile probably providing immune effectors to intestinal mucus upon inflammation was deduced. Specifically, many key immune transcripts in gut or liver as well as key immune proteins in mucus or bile were demonstrated. Accordingly, we proposed a hypothesized profile of fish gut-liver immunity, during either homeostasis or inflammation. Current data suggested that fish gut and liver may collaborate immunologically while keep homeostasis using own strategies, including potential unique mechanisms.

Genome Investigations of Vector Competence in Aedes aegypti to Inform Novel Arbovirus Disease Control Approaches

PubMed Central

Severson, David W.; Behura, Susanta K.

2016-01-01

Dengue (DENV), yellow fever, chikungunya, and Zika virus transmission to humans by a mosquito host is confounded by both intrinsic and extrinsic variables. Besides virulence factors of the individual arboviruses, likelihood of virus transmission is subject to variability in the genome of the primary mosquito vector, Aedes aegypti. The “vectorial capacity” of A. aegypti varies depending upon its density, biting rate, and survival rate, as well as its intrinsic ability to acquire, host and transmit a given arbovirus. This intrinsic ability is known as “vector competence”. Based on whole transcriptome analysis, several genes and pathways have been predicated to have an association with a susceptible or refractory response in A. aegypti to DENV infection. However, the functional genomics of vector competence of A. aegypti is not well understood, primarily due to lack of integrative approaches in genomic or transcriptomic studies. In this review, we focus on the present status of genomics studies of DENV vector competence in A. aegypti as limited information is available relative to the other arboviruses. We propose future areas of research needed to facilitate the integration of vector and virus genomics and environmental factors to work towards better understanding of vector competence and vectorial capacity in natural conditions. PMID:27809220

Tapping the Power of Crustacean Transcriptomics to Address Grand Challenges in Comparative Biology: An Introduction to the Symposium.

PubMed

Mykles, Donald L; Burnett, Karen G; Durica, David S; Stillman, Jonathon H

2016-12-01

Crustaceans, and decapods in particular (i.e., crabs, shrimp, and lobsters), are a diverse and ecologically and commercially important group of organisms. Understanding responses to abiotic and biotic factors is critical for developing best practices in aquaculture and assessing the effects of changing environments on the biology of these important animals. A relatively small number of decapod crustacean species have been intensively studied at the molecular level; the availability, experimental tractability, and economic relevance factor into the selection of a particular species as a model. Transcriptomics, using high-throughput next generation sequencing (NGS, coupled with RNA sequencing or RNA-seq) is revolutionizing crustacean biology. The 11 symposium papers in this volume illustrate how RNA-seq is being used to study stress response, molting and limb regeneration, immunity and disease, reproduction and development, neurobiology, and ecology and evolution. This symposium occurred on the 10th anniversary of the symposium, "Genomic and Proteomic Approaches to Crustacean Biology", held at the Society for Integrative and Comparative Biology 2006 meeting. Two participants in the 2006 symposium, the late Paul Gross and David Towle, were recognized as leaders who pioneered the use of molecular techniques that would ultimately foster the transcriptomics research reviewed in this volume. RNA-seq is a powerful tool for hypothesis-driven research, as well as an engine for discovery. It has eclipsed the technologies available in 2006, such as microarrays, expressed sequence tags, and subtractive hybridization screening, as the millions of "reads" from NGS enable researchers to de novo assemble a comprehensive transcriptome without a complete genome sequence. The symposium series concludes with a policy paper that gives an overview of the resources available and makes recommendations for developing better tools for functional annotation and pathway and network analysis in organisms in which the genome is not available or is incomplete. © The Author 2016. Published by Oxford University Press on behalf of the Society for Integrative and Comparative Biology. All rights reserved. For permissions please email: journals.permissions@oup.com.

Integrating Transcriptomic and Proteomic Data Using Predictive Regulatory Network Models of Host Response to Pathogens

PubMed Central

Chasman, Deborah; Walters, Kevin B.; Lopes, Tiago J. S.; Eisfeld, Amie J.; Kawaoka, Yoshihiro; Roy, Sushmita

2016-01-01

Mammalian host response to pathogenic infections is controlled by a complex regulatory network connecting regulatory proteins such as transcription factors and signaling proteins to target genes. An important challenge in infectious disease research is to understand molecular similarities and differences in mammalian host response to diverse sets of pathogens. Recently, systems biology studies have produced rich collections of omic profiles measuring host response to infectious agents such as influenza viruses at multiple levels. To gain a comprehensive understanding of the regulatory network driving host response to multiple infectious agents, we integrated host transcriptomes and proteomes using a network-based approach. Our approach combines expression-based regulatory network inference, structured-sparsity based regression, and network information flow to infer putative physical regulatory programs for expression modules. We applied our approach to identify regulatory networks, modules and subnetworks that drive host response to multiple influenza infections. The inferred regulatory network and modules are significantly enriched for known pathways of immune response and implicate apoptosis, splicing, and interferon signaling processes in the differential response of viral infections of different pathogenicities. We used the learned network to prioritize regulators and study virus and time-point specific networks. RNAi-based knockdown of predicted regulators had significant impact on viral replication and include several previously unknown regulators. Taken together, our integrated analysis identified novel module level patterns that capture strain and pathogenicity-specific patterns of expression and helped identify important regulators of host response to influenza infection. PMID:27403523

Relationships between drought, heat and air humidity responses revealed by transcriptome-metabolome co-analysis.

PubMed

Georgii, Elisabeth; Jin, Ming; Zhao, Jin; Kanawati, Basem; Schmitt-Kopplin, Philippe; Albert, Andreas; Winkler, J Barbro; Schäffner, Anton R

2017-07-10

Elevated temperature and reduced water availability are frequently linked abiotic stresses that may provoke distinct as well as interacting molecular responses. Based on non-targeted metabolomic and transcriptomic measurements from Arabidopsis rosettes, this study aims at a systematic elucidation of relevant components in different drought and heat scenarios as well as relationships between molecular players of stress response. In combined drought-heat stress, the majority of single stress responses are maintained. However, interaction effects between drought and heat can be discovered as well; these relate to protein folding, flavonoid biosynthesis and growth inhibition, which are enhanced, reduced or specifically induced in combined stress, respectively. Heat stress experiments with and without supplementation of air humidity for maintenance of vapor pressure deficit suggest that decreased relative air humidity due to elevated temperature is an important component of heat stress, specifically being responsible for hormone-related responses to water deprivation. Remarkably, this "dry air effect" is the primary trigger of the metabolomic response to heat. In contrast, the transcriptomic response has a substantial temperature component exceeding the dry air component and including up-regulation of many transcription factors and protein folding-related genes. Data level integration independent of prior knowledge on pathways and condition labels reveals shared drought and heat responses between transcriptome and metabolome, biomarker candidates and co-regulation between genes and metabolic compounds, suggesting novel players in abiotic stress response pathways. Drought and heat stress interact both at transcript and at metabolite response level. A comprehensive, non-targeted view of this interaction as well as non-interacting processes is important to be taken into account when improving tolerance to abiotic stresses in breeding programs. Transcriptome and metabolome may respond with different extent to individual stress components. Their contrasting behavior in response to temperature stress highlights that the protein folding machinery effectively shields the metabolism from stress. Disentangling the complex relationships between transcriptome and metabolome in response to stress is an enormous challenge. As demonstrated by case studies with supporting evidence from additional data, the large dataset provided in this study may assist in determining linked genetic and metabolic features as candidates for future mechanistic analyses.

E-Flux2 and SPOT: Validated Methods for Inferring Intracellular Metabolic Flux Distributions from Transcriptomic Data.

PubMed

Kim, Min Kyung; Lane, Anatoliy; Kelley, James J; Lun, Desmond S

2016-01-01

Several methods have been developed to predict system-wide and condition-specific intracellular metabolic fluxes by integrating transcriptomic data with genome-scale metabolic models. While powerful in many settings, existing methods have several shortcomings, and it is unclear which method has the best accuracy in general because of limited validation against experimentally measured intracellular fluxes. We present a general optimization strategy for inferring intracellular metabolic flux distributions from transcriptomic data coupled with genome-scale metabolic reconstructions. It consists of two different template models called DC (determined carbon source model) and AC (all possible carbon sources model) and two different new methods called E-Flux2 (E-Flux method combined with minimization of l2 norm) and SPOT (Simplified Pearson cOrrelation with Transcriptomic data), which can be chosen and combined depending on the availability of knowledge on carbon source or objective function. This enables us to simulate a broad range of experimental conditions. We examined E. coli and S. cerevisiae as representative prokaryotic and eukaryotic microorganisms respectively. The predictive accuracy of our algorithm was validated by calculating the uncentered Pearson correlation between predicted fluxes and measured fluxes. To this end, we compiled 20 experimental conditions (11 in E. coli and 9 in S. cerevisiae), of transcriptome measurements coupled with corresponding central carbon metabolism intracellular flux measurements determined by 13C metabolic flux analysis (13C-MFA), which is the largest dataset assembled to date for the purpose of validating inference methods for predicting intracellular fluxes. In both organisms, our method achieves an average correlation coefficient ranging from 0.59 to 0.87, outperforming a representative sample of competing methods. Easy-to-use implementations of E-Flux2 and SPOT are available as part of the open-source package MOST (http://most.ccib.rutgers.edu/). Our method represents a significant advance over existing methods for inferring intracellular metabolic flux from transcriptomic data. It not only achieves higher accuracy, but it also combines into a single method a number of other desirable characteristics including applicability to a wide range of experimental conditions, production of a unique solution, fast running time, and the availability of a user-friendly implementation.

Transcriptome Analysis of Barbarea vulgaris Infested with Diamondback Moth (Plutella xylostella) Larvae

PubMed Central

Shen, Di; Wang, Haiping; Wu, Qingjun; Lu, Peng; Qiu, Yang; Song, Jiangping; Zhang, Youjun; Li, Xixiang

2013-01-01

Background The diamondback moth (DBM, Plutella xylostella) is a crucifer-specific pest that causes significant crop losses worldwide. Barbarea vulgaris (Brassicaceae) can resist DBM and other herbivorous insects by producing feeding-deterrent triterpenoid saponins. Plant breeders have long aimed to transfer this insect resistance to other crops. However, a lack of knowledge on the biosynthetic pathways and regulatory networks of these insecticidal saponins has hindered their practical application. A pyrosequencing-based transcriptome analysis of B. vulgaris during DBM larval feeding was performed to identify genes and gene networks responsible for saponin biosynthesis and its regulation at the genome level. Principal Findings Approximately 1.22, 1.19, 1.16, 1.23, 1.16, 1.20, and 2.39 giga base pairs of clean nucleotides were generated from B. vulgaris transcriptomes sampled 1, 4, 8, 12, 24, and 48 h after onset of P. xylostella feeding and from non-inoculated controls, respectively. De novo assembly using all data of the seven transcriptomes generated 39,531 unigenes. A total of 37,780 (95.57%) unigenes were annotated, 14,399 of which were assigned to one or more gene ontology terms and 19,620 of which were assigned to 126 known pathways. Expression profiles revealed 2,016–4,685 up-regulated and 557–5188 down-regulated transcripts. Secondary metabolic pathways, such as those of terpenoids, glucosinolates, and phenylpropanoids, and its related regulators were elevated. Candidate genes for the triterpene saponin pathway were found in the transcriptome. Orthological analysis of the transcriptome with four other crucifer transcriptomes identified 592 B. vulgaris-specific gene families with a P-value cutoff of 1e−5. Conclusion This study presents the first comprehensive transcriptome analysis of B. vulgaris subjected to a series of DBM feedings. The biosynthetic and regulatory pathways of triterpenoid saponins and other DBM deterrent metabolites in this plant were classified. The results of this study will provide useful data for future investigations on pest-resistance phytochemistry and plant breeding. PMID:23696897

Transcriptome difference and potential crosstalk between liver and mammary tissue in mid-lactation primiparous dairy cows.

PubMed

Bu, Dengpan; Bionaz, Massimo; Wang, Mengzhi; Nan, Xuemei; Ma, Lu; Wang, Jiaqi

2017-01-01

Liver and mammary gland are among the most important organs during lactation in dairy cows. With the purpose of understanding both the different and the complementary roles and the crosstalk of those two organs during lactation, a transcriptome analysis was performed on liver and mammary tissues of 10 primiparous dairy cows in mid-lactation. The analysis was performed using a 4×44K Bovine Agilent microarray chip. The transcriptome difference between the two tissues was analyzed using SAS JMP Genomics using ANOVA with a false discovery rate correction (FDR). The analysis uncovered >9,000 genes differentially expressed (DEG) between the two tissues with a FDR<0.001. The functional analysis of the DEG uncovered a larger metabolic (especially related to lipid) and inflammatory response capacity in liver compared with mammary tissue while the mammary tissue had a larger protein synthesis and secretion, proliferation/differentiation, signaling, and innate immune system capacity compared with the liver. A plethora of endogenous compounds, cytokines, and transcription factors were estimated to control the DEG between the two tissues. Compared with mammary tissue, the liver transcriptome appeared to be under control of a large array of ligand-dependent nuclear receptors and, among endogenous chemical, fatty acids and bacteria-derived compounds. Compared with liver, the transcriptome of the mammary tissue was potentially under control of a large number of growth factors and miRNA. The in silico crosstalk analysis between the two tissues revealed an overall large communication with a reciprocal control of lipid metabolism, innate immune system adaptation, and proliferation/differentiation. In summary the transcriptome analysis confirmed prior known differences between liver and mammary tissue, especially considering the indication of a larger metabolic activity in liver compared with the mammary tissue and the larger protein synthesis, communication, and proliferative capacity in mammary tissue compared with the liver. Relatively novel is the indication by the data that the transcriptome of the liver is highly regulated by dietary and bacteria-related compounds while the mammary transcriptome is more under control of hormones, growth factors, and miRNA. A large crosstalk between the two tissues with a reciprocal control of metabolism and innate immune-adaptation was indicated by the network analysis that allowed uncovering previously unknown crosstalk between liver and mammary tissue for several signaling molecules.

Transcriptome difference and potential crosstalk between liver and mammary tissue in mid-lactation primiparous dairy cows

PubMed Central

Bu, Dengpan; Bionaz, Massimo; Wang, Mengzhi; Nan, Xuemei; Ma, Lu; Wang, Jiaqi

2017-01-01

Liver and mammary gland are among the most important organs during lactation in dairy cows. With the purpose of understanding both the different and the complementary roles and the crosstalk of those two organs during lactation, a transcriptome analysis was performed on liver and mammary tissues of 10 primiparous dairy cows in mid-lactation. The analysis was performed using a 4×44K Bovine Agilent microarray chip. The transcriptome difference between the two tissues was analyzed using SAS JMP Genomics using ANOVA with a false discovery rate correction (FDR). The analysis uncovered >9,000 genes differentially expressed (DEG) between the two tissues with a FDR<0.001. The functional analysis of the DEG uncovered a larger metabolic (especially related to lipid) and inflammatory response capacity in liver compared with mammary tissue while the mammary tissue had a larger protein synthesis and secretion, proliferation/differentiation, signaling, and innate immune system capacity compared with the liver. A plethora of endogenous compounds, cytokines, and transcription factors were estimated to control the DEG between the two tissues. Compared with mammary tissue, the liver transcriptome appeared to be under control of a large array of ligand-dependent nuclear receptors and, among endogenous chemical, fatty acids and bacteria-derived compounds. Compared with liver, the transcriptome of the mammary tissue was potentially under control of a large number of growth factors and miRNA. The in silico crosstalk analysis between the two tissues revealed an overall large communication with a reciprocal control of lipid metabolism, innate immune system adaptation, and proliferation/differentiation. In summary the transcriptome analysis confirmed prior known differences between liver and mammary tissue, especially considering the indication of a larger metabolic activity in liver compared with the mammary tissue and the larger protein synthesis, communication, and proliferative capacity in mammary tissue compared with the liver. Relatively novel is the indication by the data that the transcriptome of the liver is highly regulated by dietary and bacteria-related compounds while the mammary transcriptome is more under control of hormones, growth factors, and miRNA. A large crosstalk between the two tissues with a reciprocal control of metabolism and innate immune-adaptation was indicated by the network analysis that allowed uncovering previously unknown crosstalk between liver and mammary tissue for several signaling molecules. PMID:28291785

Coccidian Merozoite Transcriptome Analysis From Eimeria Maxima In Comparison To Eimeria Tenella And Eimeria Acervulina

USDA-ARS?s Scientific Manuscript database

Using the Eimeria spp. population that infect chickens as a model for coccidian biology, we aimed to survey the transcriptome of E. maxima and contrast it to the two other Eimeria spp. for which transcriptome data are available, E. tenella and E. acervulina. Examining specifically the asexual intra...

Transcriptome profiling analysis of cultivar-specific apple fruit ripening and texture attributes

USDA-ARS?s Scientific Manuscript database

Molecular events regulating cultivar-specific apple fruit ripening and sensory quality are largely unknown. Such knowledge is essential for genomic-assisted apple breeding and postharvest quality management. In this study, transcriptome profile analysis, scanning electron microscopic examination an...

Characterizing differential gene expression in polyploid grasses lacking a reference transcriptome

USDA-ARS?s Scientific Manuscript database

Basal transcriptome characterization and differential gene expression in response to varying conditions are often addressed through next generation sequencing (NGS) and data analysis techniques. While these strategies are commonly used, there are countless tools, pipelines, data analysis methods an...

A high-throughput approach to profile RNA structure.

PubMed

Delli Ponti, Riccardo; Marti, Stefanie; Armaos, Alexandros; Tartaglia, Gian Gaetano

2017-03-17

Here we introduce the Computational Recognition of Secondary Structure (CROSS) method to calculate the structural profile of an RNA sequence (single- or double-stranded state) at single-nucleotide resolution and without sequence length restrictions. We trained CROSS using data from high-throughput experiments such as Selective 2΄-Hydroxyl Acylation analyzed by Primer Extension (SHAPE; Mouse and HIV transcriptomes) and Parallel Analysis of RNA Structure (PARS; Human and Yeast transcriptomes) as well as high-quality NMR/X-ray structures (PDB database). The algorithm uses primary structure information alone to predict experimental structural profiles with >80% accuracy, showing high performances on large RNAs such as Xist (17 900 nucleotides; Area Under the ROC Curve AUC of 0.75 on dimethyl sulfate (DMS) experiments). We integrated CROSS in thermodynamics-based methods to predict secondary structure and observed an increase in their predictive power by up to 30%. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Decoding the regulatory landscape of melanoma reveals TEADS as regulators of the invasive cell state

PubMed Central

Verfaillie, Annelien; Imrichova, Hana; Atak, Zeynep Kalender; Dewaele, Michael; Rambow, Florian; Hulselmans, Gert; Christiaens, Valerie; Svetlichnyy, Dmitry; Luciani, Flavie; Van den Mooter, Laura; Claerhout, Sofie; Fiers, Mark; Journe, Fabrice; Ghanem, Ghanem-Elias; Herrmann, Carl; Halder, Georg; Marine, Jean-Christophe; Aerts, Stein

2015-01-01

Transcriptional reprogramming of proliferative melanoma cells into a phenotypically distinct invasive cell subpopulation is a critical event at the origin of metastatic spreading. Here we generate transcriptome, open chromatin and histone modification maps of melanoma cultures; and integrate this data with existing transcriptome and DNA methylation profiles from tumour biopsies to gain insight into the mechanisms underlying this key reprogramming event. This shows thousands of genomic regulatory regions underlying the proliferative and invasive states, identifying SOX10/MITF and AP-1/TEAD as regulators, respectively. Knockdown of TEADs shows a previously unrecognized role in the invasive gene network and establishes a causative link between these transcription factors, cell invasion and sensitivity to MAPK inhibitors. Using regulatory landscapes and in silico analysis, we show that transcriptional reprogramming underlies the distinct cellular states present in melanoma. Furthermore, it reveals an essential role for the TEADs, linking it to clinically relevant mechanisms such as invasion and resistance. PMID:25865119

DBATE: database of alternative transcripts expression.

PubMed

Bianchi, Valerio; Colantoni, Alessio; Calderone, Alberto; Ausiello, Gabriele; Ferrè, Fabrizio; Helmer-Citterich, Manuela

2013-01-01

The use of high-throughput RNA sequencing technology (RNA-seq) allows whole transcriptome analysis, providing an unbiased and unabridged view of alternative transcript expression. Coupling splicing variant-specific expression with its functional inference is still an open and difficult issue for which we created the DataBase of Alternative Transcripts Expression (DBATE), a web-based repository storing expression values and functional annotation of alternative splicing variants. We processed 13 large RNA-seq panels from human healthy tissues and in disease conditions, reporting expression levels and functional annotations gathered and integrated from different sources for each splicing variant, using a variant-specific annotation transfer pipeline. The possibility to perform complex queries by cross-referencing different functional annotations permits the retrieval of desired subsets of splicing variant expression values that can be visualized in several ways, from simple to more informative. DBATE is intended as a novel tool to help appreciate how, and possibly why, the transcriptome expression is shaped. DATABASE URL: http://bioinformatica.uniroma2.it/DBATE/.

Transcriptome profiling of Galaxea fascicularis and its endosymbiont Symbiodinium reveals chronic eutrophication tolerance pathways and metabolic mutualism between partners

PubMed Central

Lin, Zhenyue; Chen, Mingliang; Dong, Xu; Zheng, Xinqing; Huang, Haining; Xu, Xun; Chen, Jianming

2017-01-01

In the South China Sea, coastal eutrophication in the Beibu Gulf has seriously threatened reef habitats by subjecting corals to chronic physiological stress. To determine how coral holobionts may tolerate such conditions, we examined the transcriptomes of healthy colonies of the galaxy coral Galaxea fascicularis and its endosymbiont Symbiodinium from two reef sites experiencing pristine or eutrophied nutrient regimes. We identified 236 and 205 genes that were differentially expressed in eutrophied hosts and symbionts, respectively. Both gene sets included pathways related to stress responses and metabolic interactions. An analysis of genes originating from each partner revealed striking metabolic integration with respect to vitamins, cofactors, amino acids, fatty acids, and secondary metabolite biosynthesis. The expression levels of these genes supported the existence of a continuum of mutualism in this coral-algal symbiosis. Additionally, large sets of transcription factors, cell signal transduction molecules, biomineralization components, and galaxin-related proteins were expanded in G. fascicularis relative to other coral species. PMID:28181581

Breast cancer genome and transcriptome integration implicates specific mutational signatures with immune cell infiltration

PubMed Central

Smid, Marcel; Rodríguez-González, F. Germán; Sieuwerts, Anieta M.; Salgado, Roberto; Prager-Van der Smissen, Wendy J. C.; Vlugt-Daane, Michelle van der; van Galen, Anne; Nik-Zainal, Serena; Staaf, Johan; Brinkman, Arie B.; van de Vijver, Marc J.; Richardson, Andrea L.; Fatima, Aquila; Berentsen, Kim; Butler, Adam; Martin, Sancha; Davies, Helen R.; Debets, Reno; Gelder, Marion E. Meijer-Van; van Deurzen, Carolien H. M.; MacGrogan, Gaëtan; Van den Eynden, Gert G. G. M.; Purdie, Colin; Thompson, Alastair M.; Caldas, Carlos; Span, Paul N.; Simpson, Peter T.; Lakhani, Sunil R.; Van Laere, Steven; Desmedt, Christine; Ringnér, Markus; Tommasi, Stefania; Eyford, Jorunn; Broeks, Annegien; Vincent-Salomon, Anne; Futreal, P. Andrew; Knappskog, Stian; King, Tari; Thomas, Gilles; Viari, Alain; Langerød, Anita; Børresen-Dale, Anne-Lise; Birney, Ewan; Stunnenberg, Hendrik G.; Stratton, Mike; Foekens, John A.; Martens, John W. M.

2016-01-01

A recent comprehensive whole genome analysis of a large breast cancer cohort was used to link known and novel drivers and substitution signatures to the transcriptome of 266 cases. Here, we validate that subtype-specific aberrations show concordant expression changes for, for example, TP53, PIK3CA, PTEN, CCND1 and CDH1. We find that CCND3 expression levels do not correlate with amplification, while increased GATA3 expression in mutant GATA3 cancers suggests GATA3 is an oncogene. In luminal cases the total number of substitutions, irrespective of type, associates with cell cycle gene expression and adverse outcome, whereas the number of mutations of signatures 3 and 13 associates with immune-response specific gene expression, increased numbers of tumour-infiltrating lymphocytes and better outcome. Thus, while earlier reports imply that the sheer number of somatic aberrations could trigger an immune-response, our data suggests that substitutions of a particular type are more effective in doing so than others. PMID:27666519

Integrative Analyses of Hepatic Differentially Expressed Genes and Blood Biomarkers during the Peripartal Period between Dairy Cows Overfed or Restricted-Fed Energy Prepartum

PubMed Central

Shahzad, Khuram; Bionaz, Massimo; Trevisi, Erminio; Bertoni, Giuseppe; Rodriguez-Zas, Sandra L.; Loor, Juan J.

2014-01-01

Using published dairy cattle liver transcriptomics dataset along with novel blood biomarkers of liver function, metabolism, and inflammation we have attempted an integrative systems biology approach applying the classical functional enrichment analysis using DAVID, a newly-developed Dynamic Impact Approach (DIA), and an upstream gene network analysis using Ingenuity Pathway Analysis (IPA). Transcriptome data was generated from experiments evaluating the impact of prepartal plane of energy intake [overfed (OF) or restricted (RE)] on liver of dairy cows during the peripartal period. Blood biomarkers uncovered that RE vs. OF led to greater prepartal liver distress accompanied by a low-grade inflammation and larger proteolysis (i.e., higher haptoglobin, bilirubin, and creatinine). Post-partum the greater bilirubinaemia and lipid accumulation in OF vs. RE indicated a large degree of liver distress. The re-analysis of microarray data revealed that expression of >4,000 genes was affected by diet × time. The bioinformatics analysis indicated that RE vs. OF cows had a liver with a greater lipid and amino acid catabolic capacity both pre- and post-partum while OF vs. RE cows had a greater activation of pathways/functions related to triglyceride synthesis. Furthermore, RE vs. OF cows had a larger (or higher capacity to cope with) ER stress likely associated with greater protein synthesis/processing, and a higher activation of inflammatory-related functions. Liver in OF vs. RE cows had a larger cell proliferation and cell-to-cell communication likely as a response to the greater lipid accumulation. Analysis of upstream regulators indicated a pivotal role of several lipid-related transcription factors (e.g., PPARs, SREBPs, and NFE2L2) in priming the liver of RE cows to better face the early postpartal metabolic and inflammatory challenges. An all-encompassing dynamic model was proposed based on the findings. PMID:24914544

Reconstruction of the Fatty Acid Biosynthetic Pathway of Exiguobacterium antarcticum B7 Based on Genomic and Bibliomic Data.

PubMed

Kawasaki, Regiane; Baraúna, Rafael A; Silva, Artur; Carepo, Marta S P; Oliveira, Rui; Marques, Rodolfo; Ramos, Rommel T J; Schneider, Maria P C

2016-01-01

Exiguobacterium antarcticum B7 is extremophile Gram-positive bacteria able to survive in cold environments. A key factor to understanding cold adaptation processes is related to the modification of fatty acids composing the cell membranes of psychrotrophic bacteria. In our study we show the in silico reconstruction of the fatty acid biosynthesis pathway of E. antarcticum B7. To build the stoichiometric model, a semiautomatic procedure was applied, which integrates genome information using KEGG and RAST/SEED. Constraint-based methods, namely, Flux Balance Analysis (FBA) and elementary modes (EM), were applied. FBA was implemented in the sense of hexadecenoic acid production maximization. To evaluate the influence of the gene expression in the fluxome analysis, FBA was also calculated using the log2⁡FC values obtained in the transcriptome analysis at 0°C and 37°C. The fatty acid biosynthesis pathway showed a total of 13 elementary flux modes, four of which showed routes for the production of hexadecenoic acid. The reconstructed pathway demonstrated the capacity of E. antarcticum B7 to de novo produce fatty acid molecules. Under the influence of the transcriptome, the fluxome was altered, promoting the production of short-chain fatty acids. The calculated models contribute to better understanding of the bacterial adaptation at cold environments.

Transcriptome profiling of a Saccharomyces cerevisiae mutant with a constitutively activated Ras/cAMP pathway.

PubMed

Jones, D L; Petty, J; Hoyle, D C; Hayes, A; Ragni, E; Popolo, L; Oliver, S G; Stateva, L I

2003-12-16

Often changes in gene expression levels have been considered significant only when above/below some arbitrarily chosen threshold. We investigated the effect of applying a purely statistical approach to microarray analysis and demonstrated that small changes in gene expression have biological significance. Whole genome microarray analysis of a pde2Delta mutant, constructed in the Saccharomyces cerevisiae reference strain FY23, revealed altered expression of approximately 11% of protein encoding genes. The mutant, characterized by constitutive activation of the Ras/cAMP pathway, has increased sensitivity to stress, reduced ability to assimilate nonfermentable carbon sources, and some cell wall integrity defects. Applying the Munich Information Centre for Protein Sequences (MIPS) functional categories revealed increased expression of genes related to ribosome biogenesis and downregulation of genes in the cell rescue, defense, cell death and aging category, suggesting a decreased response to stress conditions. A reduced level of gene expression in the unfolded protein response pathway (UPR) was observed. Cell wall genes whose expression was affected by this mutation were also identified. Several of the cAMP-responsive orphan genes, upon further investigation, revealed cell wall functions; others had previously unidentified phenotypes assigned to them. This investigation provides a statistical global transcriptome analysis of the cellular response to constitutive activation of the Ras/cAMP pathway.

Multi-omic integrated networks connect DNA methylation and miRNA with skeletal muscle plasticity to chronic exercise in Type 2 diabetic obesity

PubMed Central

Page, Rachel A.; Sukala, William R.; Giri, Mamta; Ghimbovschi, Svetlana D.; Hayat, Irum; Cheema, Birinder S.; Lys, Isabelle; Leikis, Murray; Sheard, Phillip W.; Wakefield, St. John; Breier, Bernhard; Hathout, Yetrib; Brown, Kristy; Marathi, Ramya; Orkunoglu-Suer, Funda E.; Devaney, Joseph M.; Leiken, Benjamin; Many, Gina; Krebs, Jeremy; Hopkins, Will G.; Hoffman, Eric P.

2014-01-01

Epigenomic regulation of the transcriptome by DNA methylation and posttranscriptional gene silencing by miRNAs are potential environmental modulators of skeletal muscle plasticity to chronic exercise in healthy and diseased populations. We utilized transcriptome networks to connect exercise-induced differential methylation and miRNA with functional skeletal muscle plasticity. Biopsies of the vastus lateralis were collected from middle-aged Polynesian men and women with morbid obesity (44 kg/m2 ± 10) and Type 2 diabetes before and following 16 wk of resistance (n = 9) or endurance training (n = 8). Longitudinal transcriptome, methylome, and microRNA (miRNA) responses were obtained via microarray, filtered by novel effect-size based false discovery rate probe selection preceding bioinformatic interrogation. Metabolic and microvascular transcriptome topology dominated the network landscape following endurance exercise. Lipid and glucose metabolism modules were connected to: microRNA (miR)-29a; promoter region hypomethylation of nuclear receptor factor (NRF1) and fatty acid transporter (SLC27A4), and hypermethylation of fatty acid synthase, and to exon hypomethylation of 6-phosphofructo-2-kinase and Ser/Thr protein kinase. Directional change in the endurance networks was validated by lower intramyocellular lipid, increased capillarity, GLUT4, hexokinase, and mitochondrial enzyme activity and proteome. Resistance training also lowered lipid and increased enzyme activity and caused GLUT4 promoter hypomethylation; however, training was inconsequential to GLUT4, capillarity, and metabolic transcriptome. miR-195 connected to negative regulation of vascular development. To conclude, integrated molecular network modelling revealed differential DNA methylation and miRNA expression changes occur in skeletal muscle in response to chronic exercise training that are most pronounced with endurance training and topographically associated with functional metabolic and microvascular plasticity relevant to diabetes rehabilitation. PMID:25138607

RAS oncogene-mediated deregulation of the transcriptome: from molecular signature to function.

PubMed

Schäfer, Reinhold; Sers, Christine

2011-01-01

Transcriptome analysis of cancer cells has developed into a standard procedure to elucidate multiple features of the malignant process and to link gene expression to clinical properties. Gene expression profiling based on microarrays provides essentially correlative information and needs to be transferred to the functional level in order to understand the activity and contribution of individual genes or sets of genes as elements of the gene signature. To date, there exist significant gaps in the functional understanding of gene expression profiles. Moreover, the processes that drive the profound transcriptional alterations that characterize cancer cells remain mainly elusive. We have used pathway-restricted gene expression profiles derived from RAS oncogene-transformed cells and from RAS-expressing cancer cells to identify regulators downstream of the MAPK pathway.We describe the role of epigenetic regulation exemplified by the control of several immune genes in generic cell lines and colorectal cancer cells, particularly the functional interaction between signaling and DNA methylation. Moreover, we assess the role of the architectural transcription factor high mobility AT-hook 2 (HMGA2) as a regulator of the RAS-responsive transcriptome in ovarian epithelial cells. Finally, we describe an integrated approach combining pathway interference in colorectal cancer cells, gene expression profiling and computational analysis of regulatory elements of deregulated target genes. This strategy resulted in the identification of Y-box binding protein 1 (YBX1) as a regulator of MAPK-dependent proliferation and gene expression. The implications for a therapeutic application of HMGA2 gene silencing and the role of YBX1 as a prognostic factor are discussed.

Transcriptome profiling of claw muscle of the mud crab (Scylla paramamosain) at different fattening stages

PubMed Central

Jiang, Qingling; Bao, Chenchang; Yang, Ya’nan; Liu, An; Liu, Fang; Huang, Huiyang; Ye, Haihui

2017-01-01

In crustaceans, muscle growth and development is complicated, and to date substantial knowledge gaps exist. In this study, the claw muscle, hepatopancreas and nervous tissue of the mud crab (Scylla paramamosain) were collected at three fattening stages for sequence by the Illumina sequencing. A total of 127.87 Gb clean data with no less than 3.94 Gb generated for each sample and the cycleQ30 percentages were more than 86.13% for all samples. De Bruijn assembly of these clean data produced 94,853 unigenes, thereinto, 50,059 unigenes were found in claw muscle. A total of 121 differentially expressed genes (DEGs) were revealed in claw muscle from the three fattening stages with a Padj value < 0.01, including 63 genes with annotation. Functional annotation and enrichment analysis showed that the DEGs clusters represented the predominant gene catalog with roles in biochemical processes (glycolysis, phosphorylation and regulation of transcription), molecular function (ATP binding, 6-phosphofructokinase activity, and sequence-specific DNA binding) and cellular component (6-phosphofructokinase complex, plasma membrane, and integral component of membrane). qRT-PCR was employed to further validate certain DEGs. Single nucleotide polymorphism (SNP) analysis obtained 159,322, 125,963 and 166,279 potential SNPs from the muscle transcriptome at stage B, stage C and stage D, respectively. In addition, there were sixteen neuropeptide transcripts being predicted in the claw muscle. The present study provides a comprehensive transcriptome of claw muscle of S. paramamosain during fattening, providing a basis for screening the functional genes that may affect muscle growth of S. paramamosain. PMID:29141033

Transcriptome Analysis of Human Injured Meniscus Reveals a Distinct Phenotype of Meniscus Degeneration with Aging

PubMed Central

Rai, Muhammad Farooq; Patra, Debabrata; Sandell, Linda J.; Brophy, Robert H.

2013-01-01

Objective Meniscus tears are associated with a heightened risk for osteoarthritis. We aimed to advance our understanding of the metabolic state of human injured meniscus at the time of arthroscopic partial meniscectomy through transcriptome-wide analysis of gene expression in relation to patient age and degree of cartilage chondrosis. Methods The degree of chondrosis of knee cartilage was recorded at the time of meniscectomy in symptomatic patients without radiographic osteoarthritis. RNA preparations from resected menisci (N=12) were subjected to transcriptome-wide microarray and QuantiGene Plex analyses. The relative changes in gene expression variation with age and chondrosis were analyzed and integrated biological processes were investigated computationally. Results We identified a set of genes in torn meniscus that were differentially expressed with age and chondrosis. There were 866 genes differentially regulated (≥1.5-fold; P<0.05) with age and 49 with chondrosis. In older patients, genes associated with cartilage and skeletal development and extracellular matrix synthesis were repressed while those involved in immune response, inflammation, cell cycle, and cellular proliferation were stimulated. With chondrosis, genes representing cell catabolism (cAMP catabolic process) and tissue and endothelial cell development were repressed and those involved in T cell differentiation and apoptosis were elevated. Conclusion Differences in age-related gene expression suggest that in older adults, meniscal cells might de-differentiate and initiate a proliferative phenotype. Conversely, meniscal cells in younger patients appear to respond to injury, but maintain the differentiated phenotype. Definitive molecular signatures identified in damaged meniscus could be segregated largely with age and, to a lesser extent, with chondrosis. PMID:23658108

Comparative genomics reveals conservative evolution of the xylem transcriptome in vascular plants.

PubMed

Li, Xinguo; Wu, Harry X; Southerton, Simon G

2010-06-21

Wood is a valuable natural resource and a major carbon sink. Wood formation is an important developmental process in vascular plants which played a crucial role in plant evolution. Although genes involved in xylem formation have been investigated, the molecular mechanisms of xylem evolution are not well understood. We use comparative genomics to examine evolution of the xylem transcriptome to gain insights into xylem evolution. The xylem transcriptome is highly conserved in conifers, but considerably divergent in angiosperms. The functional domains of genes in the xylem transcriptome are moderately to highly conserved in vascular plants, suggesting the existence of a common ancestral xylem transcriptome. Compared to the total transcriptome derived from a range of tissues, the xylem transcriptome is relatively conserved in vascular plants. Of the xylem transcriptome, cell wall genes, ancestral xylem genes, known proteins and transcription factors are relatively more conserved in vascular plants. A total of 527 putative xylem orthologs were identified, which are unevenly distributed across the Arabidopsis chromosomes with eight hot spots observed. Phylogenetic analysis revealed that evolution of the xylem transcriptome has paralleled plant evolution. We also identified 274 conifer-specific xylem unigenes, all of which are of unknown function. These xylem orthologs and conifer-specific unigenes are likely to have played a crucial role in xylem evolution. Conifers have highly conserved xylem transcriptomes, while angiosperm xylem transcriptomes are relatively diversified. Vascular plants share a common ancestral xylem transcriptome. The xylem transcriptomes of vascular plants are more conserved than the total transcriptomes. Evolution of the xylem transcriptome has largely followed the trend of plant evolution.

Comparative genomics reveals conservative evolution of the xylem transcriptome in vascular plants

PubMed Central

2010-01-01

Background Wood is a valuable natural resource and a major carbon sink. Wood formation is an important developmental process in vascular plants which played a crucial role in plant evolution. Although genes involved in xylem formation have been investigated, the molecular mechanisms of xylem evolution are not well understood. We use comparative genomics to examine evolution of the xylem transcriptome to gain insights into xylem evolution. Results The xylem transcriptome is highly conserved in conifers, but considerably divergent in angiosperms. The functional domains of genes in the xylem transcriptome are moderately to highly conserved in vascular plants, suggesting the existence of a common ancestral xylem transcriptome. Compared to the total transcriptome derived from a range of tissues, the xylem transcriptome is relatively conserved in vascular plants. Of the xylem transcriptome, cell wall genes, ancestral xylem genes, known proteins and transcription factors are relatively more conserved in vascular plants. A total of 527 putative xylem orthologs were identified, which are unevenly distributed across the Arabidopsis chromosomes with eight hot spots observed. Phylogenetic analysis revealed that evolution of the xylem transcriptome has paralleled plant evolution. We also identified 274 conifer-specific xylem unigenes, all of which are of unknown function. These xylem orthologs and conifer-specific unigenes are likely to have played a crucial role in xylem evolution. Conclusions Conifers have highly conserved xylem transcriptomes, while angiosperm xylem transcriptomes are relatively diversified. Vascular plants share a common ancestral xylem transcriptome. The xylem transcriptomes of vascular plants are more conserved than the total transcriptomes. Evolution of the xylem transcriptome has largely followed the trend of plant evolution. PMID:20565927

A-to-I RNA Editing Contributes to Proteomic Diversity in Cancer. | Office of Cancer Genomics

Cancer.gov

Adenosine (A) to inosine (I) RNA editing introduces many nucleotide changes in cancer transcriptomes. However, due to the complexity of post-transcriptional regulation, the contribution of RNA editing to proteomic diversity in human cancers remains unclear. Here, we performed an integrated analysis of TCGA genomic data and CPTAC proteomic data. Despite limited site diversity, we demonstrate that A-to-I RNA editing contributes to proteomic diversity in breast cancer through changes in amino acid sequences. We validate the presence of editing events at both RNA and protein levels.

Big Data Analytics in Medicine and Healthcare.

PubMed

Ristevski, Blagoj; Chen, Ming

2018-05-10

This paper surveys big data with highlighting the big data analytics in medicine and healthcare. Big data characteristics: value, volume, velocity, variety, veracity and variability are described. Big data analytics in medicine and healthcare covers integration and analysis of large amount of complex heterogeneous data such as various - omics data (genomics, epigenomics, transcriptomics, proteomics, metabolomics, interactomics, pharmacogenomics, diseasomics), biomedical data and electronic health records data. We underline the challenging issues about big data privacy and security. Regarding big data characteristics, some directions of using suitable and promising open-source distributed data processing software platform are given.

Comparative transcriptomics of early dipteran development

PubMed Central

2013-01-01

Background Modern sequencing technologies have massively increased the amount of data available for comparative genomics. Whole-transcriptome shotgun sequencing (RNA-seq) provides a powerful basis for comparative studies. In particular, this approach holds great promise for emerging model species in fields such as evolutionary developmental biology (evo-devo). Results We have sequenced early embryonic transcriptomes of two non-drosophilid dipteran species: the moth midge Clogmia albipunctata, and the scuttle fly Megaselia abdita. Our analysis includes a third, published, transcriptome for the hoverfly Episyrphus balteatus. These emerging models for comparative developmental studies close an important phylogenetic gap between Drosophila melanogaster and other insect model systems. In this paper, we provide a comparative analysis of early embryonic transcriptomes across species, and use our data for a phylogenomic re-evaluation of dipteran phylogenetic relationships. Conclusions We show how comparative transcriptomics can be used to create useful resources for evo-devo, and to investigate phylogenetic relationships. Our results demonstrate that de novo assembly of short (Illumina) reads yields high-quality, high-coverage transcriptomic data sets. We use these data to investigate deep dipteran phylogenetic relationships. Our results, based on a concatenation of 160 orthologous genes, provide support for the traditional view of Clogmia being the sister group of Brachycera (Megaselia, Episyrphus, Drosophila), rather than that of Culicomorpha (which includes mosquitoes and blackflies). PMID:23432914

BLIND ordering of large-scale transcriptomic developmental timecourses.

PubMed

Anavy, Leon; Levin, Michal; Khair, Sally; Nakanishi, Nagayasu; Fernandez-Valverde, Selene L; Degnan, Bernard M; Yanai, Itai

2014-03-01

RNA-Seq enables the efficient transcriptome sequencing of many samples from small amounts of material, but the analysis of these data remains challenging. In particular, in developmental studies, RNA-Seq is challenged by the morphological staging of samples, such as embryos, since these often lack clear markers at any particular stage. In such cases, the automatic identification of the stage of a sample would enable previously infeasible experimental designs. Here we present the 'basic linear index determination of transcriptomes' (BLIND) method for ordering samples comprising different developmental stages. The method is an implementation of a traveling salesman algorithm to order the transcriptomes according to their inter-relationships as defined by principal components analysis. To establish the direction of the ordered samples, we show that an appropriate indicator is the entropy of transcriptomic gene expression levels, which increases over developmental time. Using BLIND, we correctly recover the annotated order of previously published embryonic transcriptomic timecourses for frog, mosquito, fly and zebrafish. We further demonstrate the efficacy of BLIND by collecting 59 embryos of the sponge Amphimedon queenslandica and ordering their transcriptomes according to developmental stage. BLIND is thus useful in establishing the temporal order of samples within large datasets and is of particular relevance to the study of organisms with asynchronous development and when morphological staging is difficult.

Transcriptome Analysis at the Single-Cell Level Using SMART Technology.

PubMed

Fish, Rachel N; Bostick, Magnolia; Lehman, Alisa; Farmer, Andrew

2016-10-10

RNA sequencing (RNA-seq) is a powerful method for analyzing cell state, with minimal bias, and has broad applications within the biological sciences. However, transcriptome analysis of seemingly homogenous cell populations may in fact overlook significant heterogeneity that can be uncovered at the single-cell level. The ultra-low amount of RNA contained in a single cell requires extraordinarily sensitive and reproducible transcriptome analysis methods. As next-generation sequencing (NGS) technologies mature, transcriptome profiling by RNA-seq is increasingly being used to decipher the molecular signature of individual cells. This unit describes an ultra-sensitive and reproducible protocol to generate cDNA and sequencing libraries directly from single cells or RNA inputs ranging from 10 pg to 10 ng. Important considerations for working with minute RNA inputs are given. © 2016 by John Wiley & Sons, Inc. Copyright © 2016 John Wiley & Sons, Inc.

Integrative analysis of omics summary data reveals putative mechanisms underlying complex traits.

PubMed

Wu, Yang; Zeng, Jian; Zhang, Futao; Zhu, Zhihong; Qi, Ting; Zheng, Zhili; Lloyd-Jones, Luke R; Marioni, Riccardo E; Martin, Nicholas G; Montgomery, Grant W; Deary, Ian J; Wray, Naomi R; Visscher, Peter M; McRae, Allan F; Yang, Jian

2018-03-02

The identification of genes and regulatory elements underlying the associations discovered by GWAS is essential to understanding the aetiology of complex traits (including diseases). Here, we demonstrate an analytical paradigm of prioritizing genes and regulatory elements at GWAS loci for follow-up functional studies. We perform an integrative analysis that uses summary-level SNP data from multi-omics studies to detect DNA methylation (DNAm) sites associated with gene expression and phenotype through shared genetic effects (i.e., pleiotropy). We identify pleiotropic associations between 7858 DNAm sites and 2733 genes. These DNAm sites are enriched in enhancers and promoters, and >40% of them are mapped to distal genes. Further pleiotropic association analyses, which link both the methylome and transcriptome to 12 complex traits, identify 149 DNAm sites and 66 genes, indicating a plausible mechanism whereby the effect of a genetic variant on phenotype is mediated by genetic regulation of transcription through DNAm.

Dimension reduction techniques for the integrative analysis of multi-omics data

PubMed Central

Zeleznik, Oana A.; Thallinger, Gerhard G.; Kuster, Bernhard; Gholami, Amin M.

2016-01-01

State-of-the-art next-generation sequencing, transcriptomics, proteomics and other high-throughput ‘omics' technologies enable the efficient generation of large experimental data sets. These data may yield unprecedented knowledge about molecular pathways in cells and their role in disease. Dimension reduction approaches have been widely used in exploratory analysis of single omics data sets. This review will focus on dimension reduction approaches for simultaneous exploratory analyses of multiple data sets. These methods extract the linear relationships that best explain the correlated structure across data sets, the variability both within and between variables (or observations) and may highlight data issues such as batch effects or outliers. We explore dimension reduction techniques as one of the emerging approaches for data integration, and how these can be applied to increase our understanding of biological systems in normal physiological function and disease. PMID:26969681

Inhalation toxicity of indoor air pollutants in Drosophila melanogaster using integrated transcriptomics and computational behavior analyses

NASA Astrophysics Data System (ADS)

Eom, Hyun-Jeong; Liu, Yuedan; Kwak, Gyu-Suk; Heo, Muyoung; Song, Kyung Seuk; Chung, Yun Doo; Chon, Tae-Soo; Choi, Jinhee

2017-06-01

We conducted an inhalation toxicity test on the alternative animal model, Drosophila melanogaster, to investigate potential hazards of indoor air pollution. The inhalation toxicity of toluene and formaldehyde was investigated using comprehensive transcriptomics and computational behavior analyses. The ingenuity pathway analysis (IPA) based on microarray data suggests the involvement of pathways related to immune response, stress response, and metabolism in formaldehyde and toluene exposure based on hub molecules. We conducted a toxicity test using mutants of the representative genes in these pathways to explore the toxicological consequences of alterations of these pathways. Furthermore, extensive computational behavior analysis showed that exposure to either toluene or formaldehyde reduced most of the behavioral parameters of both wild-type and mutants. Interestingly, behavioral alteration caused by toluene or formaldehyde exposure was most severe in the p38b mutant, suggesting that the defects in the p38 pathway underlie behavioral alteration. Overall, the results indicate that exposure to toluene and formaldehyde via inhalation causes severe toxicity in Drosophila, by inducing significant alterations in gene expression and behavior, suggesting that Drosophila can be used as a potential alternative model in inhalation toxicity screening.

Transcriptional atlas of cardiogenesis maps congenital heart disease interactome.

PubMed

Li, Xing; Martinez-Fernandez, Almudena; Hartjes, Katherine A; Kocher, Jean-Pierre A; Olson, Timothy M; Terzic, Andre; Nelson, Timothy J

2014-07-01

Mammalian heart development is built on highly conserved molecular mechanisms with polygenetic perturbations resulting in a spectrum of congenital heart diseases (CHD). However, knowledge of cardiogenic ontogeny that regulates proper cardiogenesis remains largely based on candidate-gene approaches. Mapping the dynamic transcriptional landscape of cardiogenesis from a genomic perspective is essential to integrate the knowledge of heart development into translational applications that accelerate disease discovery efforts toward mechanistic-based treatment strategies. Herein, we designed a time-course transcriptome analysis to investigate the genome-wide dynamic expression landscape of innate murine cardiogenesis ranging from embryonic stem cells to adult cardiac structures. This comprehensive analysis generated temporal and spatial expression profiles, revealed stage-specific gene functions, and mapped the dynamic transcriptome of cardiogenesis to curated pathways. Reconciling known genetic underpinnings of CHD, we deconstructed a disease-centric dynamic interactome encoded within this cardiogenic atlas to identify stage-specific developmental disturbances clustered on regulation of epithelial-to-mesenchymal transition (EMT), BMP signaling, NF-AT signaling, TGFb-dependent EMT, and Notch signaling. Collectively, this cardiogenic transcriptional landscape defines the time-dependent expression of cardiac ontogeny and prioritizes regulatory networks at the interface between health and disease. Copyright © 2014 the American Physiological Society.

Inhalation toxicity of indoor air pollutants in Drosophila melanogaster using integrated transcriptomics and computational behavior analyses

PubMed Central

Eom, Hyun-Jeong; Liu, Yuedan; Kwak, Gyu-Suk; Heo, Muyoung; Song, Kyung Seuk; Chung, Yun Doo; Chon, Tae-Soo; Choi, Jinhee

2017-01-01

We conducted an inhalation toxicity test on the alternative animal model, Drosophila melanogaster, to investigate potential hazards of indoor air pollution. The inhalation toxicity of toluene and formaldehyde was investigated using comprehensive transcriptomics and computational behavior analyses. The ingenuity pathway analysis (IPA) based on microarray data suggests the involvement of pathways related to immune response, stress response, and metabolism in formaldehyde and toluene exposure based on hub molecules. We conducted a toxicity test using mutants of the representative genes in these pathways to explore the toxicological consequences of alterations of these pathways. Furthermore, extensive computational behavior analysis showed that exposure to either toluene or formaldehyde reduced most of the behavioral parameters of both wild-type and mutants. Interestingly, behavioral alteration caused by toluene or formaldehyde exposure was most severe in the p38b mutant, suggesting that the defects in the p38 pathway underlie behavioral alteration. Overall, the results indicate that exposure to toluene and formaldehyde via inhalation causes severe toxicity in Drosophila, by inducing significant alterations in gene expression and behavior, suggesting that Drosophila can be used as a potential alternative model in inhalation toxicity screening. PMID:28621308

Profiles of metabolites and gene expression in rats with chemically induced hepatic necrosis.

PubMed

Heijne, Wilbert H M; Lamers, Robert-Jan A N; van Bladeren, Peter J; Groten, John P; van Nesselrooij, Joop H J; van Ommen, Ben

2005-01-01

This study investigated whether integrated analysis of transcriptomics and metabolomics data increased the sensitivity of detection and provided new insight in the mechanisms of hepatotoxicity. Metabolite levels in plasma or urine were analyzed in relation to changes in hepatic gene expression in rats that received bromobenzene to induce acute hepatic centrilobular necrosis. Bromobenzene-induced lesions were only observed after treatment with the highest of 3 dose levels. Multivariate statistical analysis showed that metabolite profiles of blood plasma were largely different from controls when the rats were treated with bromobenzene, also at doses that did not elicit histopathological changes. Changes in levels of genes and metabolites were related to the degree of necrosis, providing putative novel markers of hepatotoxicity. Levels of endogenous metabolites like alanine, lactate, tyrosine and dimethylglycine differed in plasma from treated and control rats. The metabolite profiles of urine were found to be reflective of the exposure levels. This integrated analysis of hepatic transcriptomics and plasma metabolomics was able to more sensitively detect changes related to hepatotoxicity and discover novel markers. The relation between gene expression and metabolite levels was explored and additional insight in the role of various biological pathways in bromobenzene-induced hepatic necrosis was obtained, including the involvement of apoptosis and changes in glycolysis and amino acid metabolism. The complete Table 2 is available as a supplemental file online at http://taylorandfrancis.metapress.com/openurlasp?genre=journal&issn=0192-6233. To access the file, click on the issue link for 33(4), then select this article. A download option appears at the bottom of this abstract. In order to access the full article online, you must either have an individual subscription or a member subscription accessed through www.toxpath.org.

Integrative Transcriptomic Analysis Uncovers Novel Gene Modules That Underlie the Sulfate Response in Arabidopsis thaliana

PubMed Central

Henríquez-Valencia, Carlos; Arenas-M, Anita; Medina, Joaquín; Canales, Javier

2018-01-01

Sulfur is an essential nutrient for plant growth and development. Sulfur is a constituent of proteins, the plasma membrane and cell walls, among other important cellular components. To obtain new insights into the gene regulatory networks underlying the sulfate response, we performed an integrative meta-analysis of transcriptomic data from five different sulfate experiments available in public databases. This bioinformatic approach allowed us to identify a robust set of genes whose expression depends only on sulfate availability, indicating that those genes play an important role in the sulfate response. In relation to sulfate metabolism, the biological function of approximately 45% of these genes is currently unknown. Moreover, we found several consistent Gene Ontology terms related to biological processes that have not been extensively studied in the context of the sulfate response; these processes include cell wall organization, carbohydrate metabolism, nitrogen compound transport, and the regulation of proteolysis. Gene co-expression network analyses revealed relationships between the sulfate-responsive genes that were distributed among seven function-specific co-expression modules. The most connected genes in the sulfate co-expression network belong to a module related to the carbon response, suggesting that this biological function plays an important role in the control of the sulfate response. Temporal analyses of the network suggest that sulfate starvation generates a biphasic response, which involves that major changes in gene expression occur during both the early and late responses. Network analyses predicted that the sulfate response is regulated by a limited number of transcription factors, including MYBs, bZIPs, and NF-YAs. In conclusion, our analysis identified new candidate genes and provided new hypotheses to advance our understanding of the transcriptional regulation of sulfate metabolism in plants. PMID:29692794

Integrative Transcriptomic Analysis Uncovers Novel Gene Modules That Underlie the Sulfate Response in Arabidopsis thaliana.

PubMed

Henríquez-Valencia, Carlos; Arenas-M, Anita; Medina, Joaquín; Canales, Javier

2018-01-01

Sulfur is an essential nutrient for plant growth and development. Sulfur is a constituent of proteins, the plasma membrane and cell walls, among other important cellular components. To obtain new insights into the gene regulatory networks underlying the sulfate response, we performed an integrative meta-analysis of transcriptomic data from five different sulfate experiments available in public databases. This bioinformatic approach allowed us to identify a robust set of genes whose expression depends only on sulfate availability, indicating that those genes play an important role in the sulfate response. In relation to sulfate metabolism, the biological function of approximately 45% of these genes is currently unknown. Moreover, we found several consistent Gene Ontology terms related to biological processes that have not been extensively studied in the context of the sulfate response; these processes include cell wall organization, carbohydrate metabolism, nitrogen compound transport, and the regulation of proteolysis. Gene co-expression network analyses revealed relationships between the sulfate-responsive genes that were distributed among seven function-specific co-expression modules. The most connected genes in the sulfate co-expression network belong to a module related to the carbon response, suggesting that this biological function plays an important role in the control of the sulfate response. Temporal analyses of the network suggest that sulfate starvation generates a biphasic response, which involves that major changes in gene expression occur during both the early and late responses. Network analyses predicted that the sulfate response is regulated by a limited number of transcription factors, including MYBs, bZIPs, and NF-YAs. In conclusion, our analysis identified new candidate genes and provided new hypotheses to advance our understanding of the transcriptional regulation of sulfate metabolism in plants.

Integrated Genomic Characterization Reveals Novel, Therapeutically Relevant Drug Targets in FGFR and EGFR Pathways in Sporadic Intrahepatic Cholangiocarcinoma

PubMed Central

Liang, Winnie S.; Fonseca, Rafael; Bryce, Alan H.; McCullough, Ann E.; Barrett, Michael T.; Hunt, Katherine; Patel, Maitray D.; Young, Scott W.; Collins, Joseph M.; Silva, Alvin C.; Condjella, Rachel M.; Block, Matthew; McWilliams, Robert R.; Lazaridis, Konstantinos N.; Klee, Eric W.; Bible, Keith C.; Harris, Pamela; Oliver, Gavin R.; Bhavsar, Jaysheel D.; Nair, Asha A.; Middha, Sumit; Asmann, Yan; Kocher, Jean-Pierre; Schahl, Kimberly; Kipp, Benjamin R.; Barr Fritcher, Emily G.; Baker, Angela; Aldrich, Jessica; Kurdoglu, Ahmet; Izatt, Tyler; Christoforides, Alexis; Cherni, Irene; Nasser, Sara; Reiman, Rebecca; Phillips, Lori; McDonald, Jackie; Adkins, Jonathan; Mastrian, Stephen D.; Placek, Pamela; Watanabe, Aprill T.; LoBello, Janine; Han, Haiyong; Von Hoff, Daniel; Craig, David W.; Stewart, A. Keith; Carpten, John D.

2014-01-01

Advanced cholangiocarcinoma continues to harbor a difficult prognosis and therapeutic options have been limited. During the course of a clinical trial of whole genomic sequencing seeking druggable targets, we examined six patients with advanced cholangiocarcinoma. Integrated genome-wide and whole transcriptome sequence analyses were performed on tumors from six patients with advanced, sporadic intrahepatic cholangiocarcinoma (SIC) to identify potential therapeutically actionable events. Among the somatic events captured in our analysis, we uncovered two novel therapeutically relevant genomic contexts that when acted upon, resulted in preliminary evidence of anti-tumor activity. Genome-wide structural analysis of sequence data revealed recurrent translocation events involving the FGFR2 locus in three of six assessed patients. These observations and supporting evidence triggered the use of FGFR inhibitors in these patients. In one example, preliminary anti-tumor activity of pazopanib (in vitro FGFR2 IC50≈350 nM) was noted in a patient with an FGFR2-TACC3 fusion. After progression on pazopanib, the same patient also had stable disease on ponatinib, a pan-FGFR inhibitor (in vitro, FGFR2 IC50≈8 nM). In an independent non-FGFR2 translocation patient, exome and transcriptome analysis revealed an allele specific somatic nonsense mutation (E384X) in ERRFI1, a direct negative regulator of EGFR activation. Rapid and robust disease regression was noted in this ERRFI1 inactivated tumor when treated with erlotinib, an EGFR kinase inhibitor. FGFR2 fusions and ERRFI mutations may represent novel targets in sporadic intrahepatic cholangiocarcinoma and trials should be characterized in larger cohorts of patients with these aberrations. PMID:24550739

Unraveling the Light-Specific Metabolic and Regulatory Signatures of Rice through Combined in Silico Modeling and Multiomics Analysis1[OPEN

PubMed Central

Lim, Sun-Hyung; Kim, Jae Kwang; Ha, Sun-Hwa

2015-01-01

Light quality is an important signaling component upon which plants orchestrate various morphological processes, including seed germination and seedling photomorphogenesis. However, it is still unclear how plants, especially food crops, sense various light qualities and modulate their cellular growth and other developmental processes. Therefore, in this work, we initially profiled the transcripts of a model crop, rice (Oryza sativa), under four different light treatments (blue, green, red, and white) as well as in the dark. Concurrently, we reconstructed a fully compartmentalized genome-scale metabolic model of rice cells, iOS2164, containing 2,164 unique genes, 2,283 reactions, and 1,999 metabolites. We then combined the model with transcriptome profiles to elucidate the light-specific transcriptional signatures of rice metabolism. Clearly, light signals mediated rice gene expressions, differentially regulating numerous metabolic pathways: photosynthesis and secondary metabolism were up-regulated in blue light, whereas reserve carbohydrates degradation was pronounced in the dark. The topological analysis of gene expression data with the rice genome-scale metabolic model further uncovered that phytohormones, such as abscisate, ethylene, gibberellin, and jasmonate, are the key biomarkers of light-mediated regulation, and subsequent analysis of the associated genes’ promoter regions identified several light-specific transcription factors. Finally, the transcriptional control of rice metabolism by red and blue light signals was assessed by integrating the transcriptome and metabolome data with constraint-based modeling. The biological insights gained from this integrative systems biology approach offer several potential applications, such as improving the agronomic traits of food crops and designing light-specific synthetic gene circuits in microbial and mammalian systems. PMID:26453433

Impact of gestational chronodisruption on fetal cardiac genomics.

PubMed

Galdames, Hugo A; Torres-Farfan, Claudia; Spichiger, Carlos; Mendez, Natalia; Abarzua-Catalan, Lorena; Alonso-Vazquez, Pamela; Richter, Hans G

2014-01-01

We recently reported that gestational chronodisruption induces fetal growth restriction and marked effects on fetal adrenal physiology. Here, whole-transcriptome profiling was used to test whether gestational chronodisruption modifies gene expression in the fetal heart, potentially altering cardiac development. At day 10 of gestation (E10), pregnant rats were randomized in two groups: constant light (LL) and control 12 h light/12 h dark photoperiod (LD). RNA isolated from E18 heart was subjected to microarray analysis (Affymetrix platform for 28,000 genes). Integrated transcriptional changes were assessed by gene ontology and pathway analysis. Significant differential expression was found for 383 transcripts in LL relative to LD fetal heart (280 up-regulated and 103 down-regulated); with 42 of them displaying a 1.5-fold or greater change in gene expression. Deregulated markers of cardiovascular disease accounted for alteration of diverse gene networks in LL fetal heart, including local steroidogenesis and vascular calcification, as well as cardiac hypertrophy, stenosis and necrosis/cell death. DNA integrity was also overrepresented, including a 2.1-fold increase of Hmga1 mRNA, which encodes for a profuse architectural transcription factor. microRNA analysis revealed up-regulation of miRNAs 218-1 and 501 and concurrent down-regulation of their validated target genes. In addition, persistent down-regulation of Kcnip2 mRNA and hypertrophy of the left ventricle were found in the heart from 90 days-old offspring from LL mothers. The dysregulation of a relevant fraction of the fetal cardiac transcriptome, together with the diversity and complexity of the gene networks altered by gestational chronodisruption, suggest enduring molecular changes which may shape the hypertrophy observed in the left ventricle of adult LL offspring. © 2013.

Establishment of Functional Genomics Pipeline in Mouse Epiblast-Like Tissue by Combining Transcriptomic Analysis and Gene Knockdown/Knockin/Knockout, Using RNA Interference and CRISPR/Cas9.

PubMed

Takata, Nozomu; Sakakura, Eriko; Kasukawa, Takeya; Sakuma, Tetsushi; Yamamoto, Takashi; Sasai, Yoshiki

2016-06-01

The epiblast (foremost embryonic ectoderm) generates all three germ layers and therefore has crucial roles in the formation of all mammalian body cells. However, regulation of epiblast gene expression is poorly understood because of the difficulty of manipulating epiblast tissues in vivo. In the present study, using the self-organizing properties of mouse embryonic stem cell (ESC), we generated and characterized epiblast-like tissue in three-dimensional culture. We identified significant genome-wide gene expression changes in this epiblast-like tissue by transcriptomic analysis. In addition, we identified the particular significance of the Erk/Mapk and integrin-linked kinase pathways, and genes related to ectoderm/epithelial formation, using the bioinformatics resources IPA and DAVID. Here, we focused on Fgf5, which ranked in the top 10 among the discovered genes. To develop a functional analysis of Fgf5, we created an efficient method combining CRISPR/Cas9-mediated genome engineering and RNA interference (RNAi). Notably, we show one-step generation of various Fgf5 reporter lines including heterozygous and homozygous knockins (the GET method). For time- and dose-dependent depletion of fgf5 over the course of development, we generated an ESC line harboring Tol2 transposon-mediated integration of an inducible short hairpin RNA interference system (pdiRNAi). Our findings raised the possibility that Fgf/Erk signaling and apicobasal epithelial integrity are important factors in epiblast development. In addition, our methods provide a framework for a broad array of applications in the areas of mammalian genetics and molecular biology to understand development and to improve future therapeutics.

Transcriptomic analysis of persistent infection with foot-and-mouth disease virus in cattle suggests impairment of cell-mediated immunity in the nasopharynx

USDA-ARS?s Scientific Manuscript database

In order to investigate the mechanisms of persistent foot-and-mouth disease virus (FMDV) infection in cattle, transcriptome alterations associated with the FMDV carrier state were characterized using a bovine whole-transcriptome microarray. Eighteen cattle (8 vaccinated with a recombinant FMDV A vac...

New approach for the study of mite reproduction: the first transcriptome analysis of a mite, Phytoseiulus persimilis (Acari: Phytoseiidae)

USDA-ARS?s Scientific Manuscript database

Many species of mites and ticks are of agricultural and medical importance. Much can be learned from the study of transcriptomes of acarines which can generate DNA-sequence information of potential target genes for the control of acarine pests. High throughput transcriptome sequencing can also yie...

TranslatomeDB: a comprehensive database and cloud-based analysis platform for translatome sequencing data

PubMed Central

Liu, Wanting; Xiang, Lunping; Zheng, Tingkai; Jin, Jingjie

2018-01-01

Abstract Translation is a key regulatory step, linking transcriptome and proteome. Two major methods of translatome investigations are RNC-seq (sequencing of translating mRNA) and Ribo-seq (ribosome profiling). To facilitate the investigation of translation, we built a comprehensive database TranslatomeDB (http://www.translatomedb.net/) which provides collection and integrated analysis of published and user-generated translatome sequencing data. The current version includes 2453 Ribo-seq, 10 RNC-seq and their 1394 corresponding mRNA-seq datasets in 13 species. The database emphasizes the analysis functions in addition to the dataset collections. Differential gene expression (DGE) analysis can be performed between any two datasets of same species and type, both on transcriptome and translatome levels. The translation indices translation ratios, elongation velocity index and translational efficiency can be calculated to quantitatively evaluate translational initiation efficiency and elongation velocity, respectively. All datasets were analyzed using a unified, robust, accurate and experimentally-verifiable pipeline based on the FANSe3 mapping algorithm and edgeR for DGE analyzes. TranslatomeDB also allows users to upload their own datasets and utilize the identical unified pipeline to analyze their data. We believe that our TranslatomeDB is a comprehensive platform and knowledgebase on translatome and proteome research, releasing the biologists from complex searching, analyzing and comparing huge sequencing data without needing local computational power. PMID:29106630

RNA-Seq Atlas of Glycine max: a guide to the soybean transcriptome

USDA-ARS?s Scientific Manuscript database

A first analysis of the Glycine max (L.) Merr. (soybean) transcriptome using next generation sequencing technology and RNA-Sequencing (RNA-Seq) is presented. This analysis will provide an important resource for understanding transcription and gene co-regulatory networks in soybean, the most economic...

The grapevine expression atlas reveals a deep transcriptome shift driving the entire plant into a maturation program.

PubMed

Fasoli, Marianna; Dal Santo, Silvia; Zenoni, Sara; Tornielli, Giovanni Battista; Farina, Lorenzo; Zamboni, Anita; Porceddu, Andrea; Venturini, Luca; Bicego, Manuele; Murino, Vittorio; Ferrarini, Alberto; Delledonne, Massimo; Pezzotti, Mario

2012-09-01

We developed a genome-wide transcriptomic atlas of grapevine (Vitis vinifera) based on 54 samples representing green and woody tissues and organs at different developmental stages as well as specialized tissues such as pollen and senescent leaves. Together, these samples expressed ∼91% of the predicted grapevine genes. Pollen and senescent leaves had unique transcriptomes reflecting their specialized functions and physiological status. However, microarray and RNA-seq analysis grouped all the other samples into two major classes based on maturity rather than organ identity, namely, the vegetative/green and mature/woody categories. This division represents a fundamental transcriptomic reprogramming during the maturation process and was highlighted by three statistical approaches identifying the transcriptional relationships among samples (correlation analysis), putative biomarkers (O2PLS-DA approach), and sets of strongly and consistently expressed genes that define groups (topics) of similar samples (biclustering analysis). Gene coexpression analysis indicated that the mature/woody developmental program results from the reiterative coactivation of pathways that are largely inactive in vegetative/green tissues, often involving the coregulation of clusters of neighboring genes and global regulation based on codon preference. This global transcriptomic reprogramming during maturation has not been observed in herbaceous annual species and may be a defining characteristic of perennial woody plants.

Elucidating and mining the Tulipa and Lilium transcriptomes.

PubMed

Moreno-Pachon, Natalia M; Leeggangers, Hendrika A C F; Nijveen, Harm; Severing, Edouard; Hilhorst, Henk; Immink, Richard G H

2016-10-01

Genome sequencing remains a challenge for species with large and complex genomes containing extensive repetitive sequences, of which the bulbous and monocotyledonous plants tulip and lily are examples. In such a case, sequencing of only the active part of the genome, represented by the transcriptome, is a good alternative to obtain information about gene content. In this study we aimed to generate a high quality transcriptome of tulip and lily and to make this data available as an open-access resource via a user-friendly web-based interface. The Illumina HiSeq 2000 platform was applied and the transcribed RNA was sequenced from a collection of different lily and tulip tissues, respectively. In order to obtain good transcriptome coverage and to facilitate effective data mining, assembly was done using different filtering parameters for clearing out contamination and noise of the RNAseq datasets. This analysis revealed limitations of commonly applied methods and parameter settings used in de novo transcriptome assembly. The final created transcriptomes are publicly available via a user friendly Transcriptome browser ( http://www.bioinformatics.nl/bulbs/db/species/index ). The usefulness of this resource has been exemplified by a search for all potential transcription factors in lily and tulip, with special focus on the TCP transcription factor family. This analysis and other quality parameters point out the quality of the transcriptomes, which can serve as a basis for further genomics studies in lily, tulip, and bulbous plants in general.

Integrated analysis, transcriptome-lipidome, reveals the effects of INO-level (INO2 and INO4) on lipid metabolism in yeast.

PubMed

Chumnanpuen, Pramote; Nookaew, Intawat; Nielsen, Jens

2013-10-16

In the yeast Saccharomyces cerevisiae, genes containing UASINO sequences are regulated by the Ino2/Ino4 and Opi1 transcription factors, and this regulation controls lipid biosynthesis. The expression level of INO2 and INO4 genes (INO-level) at different nutrient limited conditions might lead to various responses in yeast lipid metabolism. In this study, we undertook a global study on how INO-levels (transcription level of INO2 and INO4) affect lipid metabolism in yeast and we also studied the effects of single and double deletions of the two INO-genes (deficient effect). Using 2 types of nutrient limitations (carbon and nitrogen) in chemostat cultures operated at a fixed specific growth rate of 0.1 h-1 and strains having different INO-level, we were able to see the effect on expression level of the genes involved in lipid biosynthesis and the fluxes towards the different lipid components. Through combined measurements of the transcriptome, metabolome, and lipidome it was possible to obtain a large dataset that could be used to identify how the INO-level controls lipid metabolism and also establish correlations between the different components. In this study, we undertook a global study on how INO-levels (transcription level of INO2 and INO4) affect lipid metabolism in yeast and we also studied the effects of single and double deletions of the two INO-genes (deficient effect). Using 2 types of nutrient limitations (carbon and nitrogen) in chemostat cultures operated at a fixed specific growth rate of 0.1 h-1 and strains having different INO-level, we were able to see the effect on expression level of the genes involved in lipid biosynthesis and the fluxes towards the different lipid components. Through combined measurements of the transcriptome, metabolome, and lipidome it was possible to obtain a large dataset that could be used to identify how the INO-level controls lipid metabolism and also establish correlations between the different components. Our analysis showed the strength of using a combination of transcriptome and lipidome analysis to illustrate the effect of INO-levels on phospholipid metabolism and based on our analysis we established a global regulatory map.

De novo assembly of maritime pine transcriptome: implications for forest breeding and biotechnology.

PubMed

Canales, Javier; Bautista, Rocio; Label, Philippe; Gómez-Maldonado, Josefa; Lesur, Isabelle; Fernández-Pozo, Noe; Rueda-López, Marina; Guerrero-Fernández, Dario; Castro-Rodríguez, Vanessa; Benzekri, Hicham; Cañas, Rafael A; Guevara, María-Angeles; Rodrigues, Andreia; Seoane, Pedro; Teyssier, Caroline; Morel, Alexandre; Ehrenmann, François; Le Provost, Grégoire; Lalanne, Céline; Noirot, Céline; Klopp, Christophe; Reymond, Isabelle; García-Gutiérrez, Angel; Trontin, Jean-François; Lelu-Walter, Marie-Anne; Miguel, Celia; Cervera, María Teresa; Cantón, Francisco R; Plomion, Christophe; Harvengt, Luc; Avila, Concepción; Gonzalo Claros, M; Cánovas, Francisco M

2014-04-01

Maritime pine (Pinus pinasterAit.) is a widely distributed conifer species in Southwestern Europe and one of the most advanced models for conifer research. In the current work, comprehensive characterization of the maritime pine transcriptome was performed using a combination of two different next-generation sequencing platforms, 454 and Illumina. De novo assembly of the transcriptome provided a catalogue of 26 020 unique transcripts in maritime pine trees and a collection of 9641 full-length cDNAs. Quality of the transcriptome assembly was validated by RT-PCR amplification of selected transcripts for structural and regulatory genes. Transcription factors and enzyme-encoding transcripts were annotated. Furthermore, the available sequencing data permitted the identification of polymorphisms and the establishment of robust single nucleotide polymorphism (SNP) and simple-sequence repeat (SSR) databases for genotyping applications and integration of translational genomics in maritime pine breeding programmes. All our data are freely available at SustainpineDB, the P. pinaster expressional database. Results reported here on the maritime pine transcriptome represent a valuable resource for future basic and applied studies on this ecological and economically important pine species. © 2013 Society for Experimental Biology, Association of Applied Biologists and John Wiley & Sons Ltd.

Search for sarcoidosis candidate genes by integration of data from genomic, transcriptomic and proteomic studies.

PubMed

Maver, Ales; Medica, Igor; Peterlin, Borut

2009-12-01

The search for gene candidates in multifactorial diseases such as sarcoidosis can be based on the integration of linkage association data, gene expression data, and protein profile data from genomic, transcriptomic and proteomic studies, respectively. In this study we performed a literature-based search for studies reporting such data, followed by integration of collected information. Different databases were examined--Medline, HugGE Navigator, ArrayExpress and Gene Expression Omnibus (GEO). Candidate genes were defined as genes which were reported in at least 2 different types of omics studies. Genes previously investigated in sarcoidosis were excluded from further analyses. We identified 177 genes associated with sarcoidosis as potential new candidate genes. Subsequently, 9 gene candidates identified to overlap in 2 different types of studies (genomic, transcriptomic and/or proteomic) were consistently reported in at least 3 studies: SERPINB1, FABP4, S100A8, HBEGF, IL7R, LRIG1, PTPN23, DPM2 and NUP214. These genes are involved in regulation of immune response, cellular proliferation, apoptosis, inhibition of protease activity, lipid metabolism. Exact biological functions of HBEGF, LRIG1, PTPN23, DPM2 and NUP214 remain to be completely elucidated. We propose 9 candidate genes: SERPINB1, FABP4, S100A8, HBEGF, IL7R, LRIG1, PTPN23, DPM2 and NUP214, as genes with high potential for association with sarcoidosis.

Predictive toxicology using systemic biology and liver microfluidic “on chip” approaches: Application to acetaminophen injury

DOE Office of Scientific and Technical Information (OSTI.GOV)

Prot, Jean-Matthieu; Bunescu, Andrei; Elena-Herrmann, Bénédicte

2012-03-15

We have analyzed transcriptomic, proteomic and metabolomic profiles of hepatoma cells cultivated inside a microfluidic biochip with or without acetaminophen (APAP). Without APAP, the results show an adaptive cellular response to the microfluidic environment, leading to the induction of anti-oxidative stress and cytoprotective pathways. In presence of APAP, calcium homeostasis perturbation, lipid peroxidation and cell death are observed. These effects can be attributed to APAP metabolism into its highly reactive metabolite, N-acetyl-p-benzoquinone imine (NAPQI). That toxicity pathway was confirmed by the detection of GSH-APAP, the large production of 2-hydroxybutyrate and 3-hydroxybutyrate, and methionine, cystine, and histidine consumption in the treatedmore » biochips. Those metabolites have been reported as specific biomarkers of hepatotoxicity and glutathione depletion in the literature. In addition, the integration of the metabolomic, transcriptomic and proteomic collected profiles allowed a more complete reconstruction of the APAP injury pathways. To our knowledge, this work is the first example of a global integration of microfluidic biochip data in toxicity assessment. Our results demonstrate the potential of that new approach to predictive toxicology. -- Highlights: ► We cultivated liver cells in microfluidic biochips ► We integrated transcriptomic, proteomic and metabolomics profiles ► Pathways reconstructions were proposed in control and acetaminophen treated cultures ► Biomarkers were identified ► Comparisons with in vivo studies were proposed.« less

Comparative analysis of transcriptome in two wheat genotypes with contrasting levels of drought tolerance

USDA-ARS?s Scientific Manuscript database

Drought tolerance is a complex trait that is governed by multiple genes. To identify the potential candidate genes, comparative analysis of drought stress-responsive transcriptome between drought-tolerant (Triticum aestivum Cv. C306) and drought-sensitive (Triticum aestivum Cv. WL711) genotypes was ...

Comparative transcriptome analysis during early fruit development between three seedy citrus genotypes and their seedless mutants

USDA-ARS?s Scientific Manuscript database

Identification of genes with differential transcript abundance (GDTA) in seedless mutants may enhance understanding of seedless citrus development. Transcriptome analysis was conducted at three time points during early fruit development (Phase 1) of three seedy citrus genotypes: Fallglo [Bower citru...

Genome analysis of medicinal Ganoderma spp. with plant-pathogenic and saprotrophic life-styles.

PubMed

Kües, Ursula; Nelson, David R; Liu, Chang; Yu, Guo-Jun; Zhang, Jianhui; Li, Jianqin; Wang, Xin-Cun; Sun, Hui

2015-06-01

Ganoderma is a fungal genus belonging to the Ganodermataceae family and Polyporales order. Plant-pathogenic species in this genus can cause severe diseases (stem, butt, and root rot) in economically important trees and perennial crops, especially in tropical countries. Ganoderma species are white rot fungi and have ecological importance in the breakdown of woody plants for nutrient mobilization. They possess effective machineries of lignocellulose-decomposing enzymes useful for bioenergy production and bioremediation. In addition, the genus contains many important species that produce pharmacologically active compounds used in health food and medicine. With the rapid adoption of next-generation DNA sequencing technologies, whole genome sequencing and systematic transcriptome analyses become affordable approaches to identify an organism's genes. In the last few years, numerous projects have been initiated to identify the genetic contents of several Ganoderma species, particularly in different strains of Ganoderma lucidum. In November 2013, eleven whole genome sequencing projects for Ganoderma species were registered in international databases, three of which were already completed with genomes being assembled to high quality. In addition to the nuclear genome, two mitochondrial genomes for Ganoderma species have also been reported. Complementing genome analysis, four transcriptome studies on various developmental stages of Ganoderma species have been performed. Information obtained from these studies has laid the foundation for the identification of genes involved in biological pathways that are critical for understanding the biology of Ganoderma, such as the mechanism of pathogenesis, the biosynthesis of active components, life cycle and cellular development, etc. With abundant genetic information becoming available, a few centralized resources have been established to disseminate the knowledge and integrate relevant data to support comparative genomic analyses of Ganoderma species. The current review carries out a detailed comparison of the nuclear genomes, mitochondrial genomes and transcriptomes from several Ganoderma species. Genes involved in biosynthetic pathways such as CYP450 genes and in cellular development such as matA and matB genes are characterized and compared in detail, as examples to demonstrate the usefulness of comparative genomic analyses for the identification of critical genes. Resources needed for future data integration and exploitation are also discussed. Copyright © 2014 Elsevier Ltd. All rights reserved.

Optimized approach for Ion Proton RNA sequencing reveals details of RNA splicing and editing features of the transcriptome.

PubMed

Brown, Roger B; Madrid, Nathaniel J; Suzuki, Hideaki; Ness, Scott A

2017-01-01

RNA-sequencing (RNA-seq) has become the standard method for unbiased analysis of gene expression but also provides access to more complex transcriptome features, including alternative RNA splicing, RNA editing, and even detection of fusion transcripts formed through chromosomal translocations. However, differences in library methods can adversely affect the ability to recover these different types of transcriptome data. For example, some methods have bias for one end of transcripts or rely on low-efficiency steps that limit the complexity of the resulting library, making detection of rare transcripts less likely. We tested several commonly used methods of RNA-seq library preparation and found vast differences in the detection of advanced transcriptome features, such as alternatively spliced isoforms and RNA editing sites. By comparing several different protocols available for the Ion Proton sequencer and by utilizing detailed bioinformatics analysis tools, we were able to develop an optimized random primer based RNA-seq technique that is reliable at uncovering rare transcript isoforms and RNA editing features, as well as fusion reads from oncogenic chromosome rearrangements. The combination of optimized libraries and rapid Ion Proton sequencing provides a powerful platform for the transcriptome analysis of research and clinical samples.

Assessment of pleiotropic transcriptome perturbations in Arabidopsis engineered for indirect insect defence.

PubMed

Houshyani, Benyamin; van der Krol, Alexander R; Bino, Raoul J; Bouwmeester, Harro J

2014-06-19

Molecular characterization is an essential step of risk/safety assessment of genetically modified (GM) crops. Holistic approaches for molecular characterization using omics platforms can be used to confirm the intended impact of the genetic engineering, but can also reveal the unintended changes at the omics level as a first assessment of potential risks. The potential of omics platforms for risk assessment of GM crops has rarely been used for this purpose because of the lack of a consensus reference and statistical methods to judge the significance or importance of the pleiotropic changes in GM plants. Here we propose a meta data analysis approach to the analysis of GM plants, by measuring the transcriptome distance to untransformed wild-types. In the statistical analysis of the transcriptome distance between GM and wild-type plants, values are compared with naturally occurring transcriptome distances in non-GM counterparts obtained from a database. Using this approach we show that the pleiotropic effect of genes involved in indirect insect defence traits is substantially equivalent to the variation in gene expression occurring naturally in Arabidopsis. Transcriptome distance is a useful screening method to obtain insight in the pleiotropic effects of genetic modification.

The utility of transcriptomics in fish conservation.

PubMed

Connon, Richard E; Jeffries, Ken M; Komoroske, Lisa M; Todgham, Anne E; Fangue, Nann A

2018-01-29

There is growing recognition of the need to understand the mechanisms underlying organismal resilience (i.e. tolerance, acclimatization) to environmental change to support the conservation management of sensitive and economically important species. Here, we discuss how functional genomics can be used in conservation biology to provide a cellular-level understanding of organismal responses to environmental conditions. In particular, the integration of transcriptomics with physiological and ecological research is increasingly playing an important role in identifying functional physiological thresholds predictive of compensatory responses and detrimental outcomes, transforming the way we can study issues in conservation biology. Notably, with technological advances in RNA sequencing, transcriptome-wide approaches can now be applied to species where no prior genomic sequence information is available to develop species-specific tools and investigate sublethal impacts that can contribute to population declines over generations and undermine prospects for long-term conservation success. Here, we examine the use of transcriptomics as a means of determining organismal responses to environmental stressors and use key study examples of conservation concern in fishes to highlight the added value of transcriptome-wide data to the identification of functional response pathways. Finally, we discuss the gaps between the core science and policy frameworks and how thresholds identified through transcriptomic evaluations provide evidence that can be more readily used by resource managers. © 2018. Published by The Company of Biologists Ltd.

Global Transcriptome Sequencing Reveals Molecular Profiles of Summer Diapause Induction Stage of Onion Maggot, Delia antiqua (Diptera: Anthomyiidae)

PubMed Central

Ren, Shuang; Hao, You-Jin; Chen, Bin; Yin, You-Ping

2017-01-01

The onion maggot, Delia antiqua, is a worldwide subterranean pest and can enter diapause during the summer and winter seasons. The molecular regulation of the ontogenesis transition remains largely unknown. Here we used high-throughput RNA sequencing to identify candidate genes and processes linked to summer diapause (SD) induction by comparing the transcriptome differences between the most sensitive larval developmental stage of SD and nondiapause (ND). Nine pairwise comparisons were performed, and significantly differentially regulated transcripts were identified. Several functional terms related to lipid, carbohydrate, and energy metabolism, environmental adaption, immune response, and aging were enriched during the most sensitive SD induction period. A subset of genes, including circadian clock genes, were expressed differentially under diapause induction conditions, and there was much more variation in the most sensitive period of ND- than SD-destined larvae. These expression variations probably resulted in a deep restructuring of metabolic pathways. Potential regulatory elements of SD induction including genes related to lipid, carbohydrate, energy metabolism, and environmental adaption. Collectively, our results suggest the circadian clock is one of the key drivers for integrating environmental signals into the SD induction. Our transcriptome analysis provides insight into the fundamental role of the circadian clock in SD induction in this important model insect species, and contributes to the in-depth elucidation of the molecular regulation mechanism of insect diapause induction. PMID:29158334

Alternative Splicing Substantially Diversifies the Transcriptome during Early Photomorphogenesis and Correlates with the Energy Availability in Arabidopsis.

PubMed

Hartmann, Lisa; Drewe-Boß, Philipp; Wießner, Theresa; Wagner, Gabriele; Geue, Sascha; Lee, Hsin-Chieh; Obermüller, Dominik M; Kahles, André; Behr, Jonas; Sinz, Fabian H; Rätsch, Gunnar; Wachter, Andreas

2016-11-01

Plants use light as source of energy and information to detect diurnal rhythms and seasonal changes. Sensing changing light conditions is critical to adjust plant metabolism and to initiate developmental transitions. Here, we analyzed transcriptome-wide alterations in gene expression and alternative splicing (AS) of etiolated seedlings undergoing photomorphogenesis upon exposure to blue, red, or white light. Our analysis revealed massive transcriptome reprogramming as reflected by differential expression of ∼20% of all genes and changes in several hundred AS events. For more than 60% of all regulated AS events, light promoted the production of a presumably protein-coding variant at the expense of an mRNA with nonsense-mediated decay-triggering features. Accordingly, AS of the putative splicing factor REDUCED RED-LIGHT RESPONSES IN CRY1CRY2 BACKGROUND1, previously identified as a red light signaling component, was shifted to the functional variant under light. Downstream analyses of candidate AS events pointed at a role of photoreceptor signaling only in monochromatic but not in white light. Furthermore, we demonstrated similar AS changes upon light exposure and exogenous sugar supply, with a critical involvement of kinase signaling. We propose that AS is an integration point of signaling pathways that sense and transmit information regarding the energy availability in plants. © 2016 American Society of Plant Biologists. All rights reserved.

PlanMine--a mineable resource of planarian biology and biodiversity.

PubMed

Brandl, Holger; Moon, HongKee; Vila-Farré, Miquel; Liu, Shang-Yun; Henry, Ian; Rink, Jochen C

2016-01-04

Planarian flatworms are in the midst of a renaissance as a model system for regeneration and stem cells. Besides two well-studied model species, hundreds of species exist worldwide that present a fascinating diversity of regenerative abilities, tissue turnover rates, reproductive strategies and other life history traits. PlanMine (http://planmine.mpi-cbg.de/) aims to accomplish two primary missions: First, to provide an easily accessible platform for sharing, comparing and value-added mining of planarian sequence data. Second, to catalyze the comparative analysis of the phenotypic diversity amongst planarian species. Currently, PlanMine houses transcriptomes independently assembled by our lab and community contributors. Detailed assembly/annotation statistics, a custom-developed BLAST viewer and easy export options enable comparisons at the contig and assembly level. Consistent annotation of all transcriptomes by an automated pipeline, the integration of published gene expression information and inter-relational query tools provide opportunities for mining planarian gene sequences and functions. For inter-species comparisons, we include transcriptomes of, so far, six planarian species, along with images, expert-curated information on their biology and pre-calculated cross-species sequence homologies. PlanMine is based on the popular InterMine system in order to make the rich biology of planarians accessible to the general life sciences research community. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Plant defense compounds: systems approaches to metabolic analysis.

PubMed

Kliebenstein, Daniel J

2012-01-01

Systems biology attempts to answer biological questions by integrating across diverse genomic data sets. With the increasing ability to conduct genomics experiments, this integrative approach is being rapidly applied across numerous biological research communities. One of these research communities investigates how plants utilize secondary metabolites or defense metabolites to defend against attack by pathogens and other biotic organisms. This use of systems biology to integrate across transcriptomics, metabolomics, and genomics is significantly enhancing the rate of discovery of genes, metabolites, and bioactivities for plant defense compounds as well as extending our knowledge of how these compounds are regulated. Plant defense compounds are also providing a unique proving platform to develop new approaches that enhance the ability to conduct systems biology with existing and previously unforseen genomics data sets. This review attempts to illustrate both how systems biology is helping the study of plant defense compounds and vice versa.

A comparative integrated transcript analysis and functional characterization of differential mechanisms for induction of liver hypertrophy in the rat

DOE Office of Scientific and Technical Information (OSTI.GOV)

Boitier, Eric, E-mail: eric.boitier@sanofi-aventis.com; Amberg, Alexander; Barbie, Valerie

2011-04-15

The main goal of the present work was to better understand the molecular mechanisms underlying liver hypertrophy (LH), a recurrent finding observed following acute or repeated drug administration to animals, using transcriptomic technologies together with the results from conventional toxicology methods. Administration of 5 terminated proprietary drug candidates from participating companies involved in the EU Innomed PredTox Project or the reference hepatotoxicant troglitazone to rats for up to a 14-day duration induced LH as the main liver phenotypic toxicity outcome. The integrated analysis of transcriptomic liver expression data across studies turned out to be the most informative approach for themore » generation of mechanistic models of LH. In response to a xenobiotic stimulus, a marked increase in the expression of xenobiotic metabolizing enzymes (XME) was observed in a subset of 4 studies. Accumulation of these newly-synthesized proteins within the smooth endoplasmic reticulum (SER) would suggest proliferation of this organelle, which most likely is the main molecular process underlying the LH observed in XME studies. In another subset of 2 studies (including troglitazone), a marked up-regulation of genes involved in peroxisomal fatty acid {beta}-oxidation was noted, associated with induction of genes involved in peroxisome proliferation. Therefore, an increase in peroxisome abundance would be the main mechanism underlying LH noted in this second study subset. Together, the use of transcript profiling provides a means to generate putative mechanistic models underlying the pathogenesis of liver hypertrophy, to distinguish between subtle variations in subcellular organelle proliferation and creates opportunities for improved mechanism-based risk assessment.« less

Transcript Profile of Flowering Regulatory Genes in VcFT-Overexpressing Blueberry Plants

PubMed Central

Walworth, Aaron E.; Chai, Benli; Song, Guo-qing

2016-01-01

In order to identify genetic components in flowering pathways of highbush blueberry (Vaccinium corymbosum L.), a transcriptome reference composed of 254,396 transcripts and 179,853 gene contigs was developed by assembly of 72.7 million reads using Trinity. Using this transcriptome reference and a query of flowering pathway genes of herbaceous plants, we identified potential flowering pathway genes/transcripts of blueberry. Transcriptome analysis of flowering pathway genes was then conducted on leaf tissue samples of transgenic blueberry cv. Aurora (‘VcFT-Aurora’), which overexpresses a blueberry FLOWERING LOCUS T-like gene (VcFT). Sixty-one blueberry transcripts of 40 genes showed high similarities to 33 known flowering-related genes of herbaceous plants, of which 17 down-regulated and 16 up-regulated genes were identified in ‘VcFT-Aurora’. All down-regulated genes encoded transcription factors/enzymes upstream in the signaling pathway containing VcFT. A blueberry CONSTANS-LIKE 5-like (VcCOL5) gene was down-regulated and associated with five other differentially expressed (DE) genes in the photoperiod-mediated flowering pathway. Three down-regulated genes, i.e., a MADS-AFFECTING FLOWERING 2-like gene (VcMAF2), a MADS-AFFECTING FLOWERING 5-like gene (VcMAF5), and a VERNALIZATION1-like gene (VcVRN1), may function as integrators in place of FLOWERING LOCUS C (FLC) in the vernalization pathway. Because no CONSTAN1-like or FLOWERING LOCUS C-like genes were found in blueberry, VcCOL5 and VcMAF2/VcMAF5 or VRN1 might be the major integrator(s) in the photoperiod- and vernalization-mediated flowering pathway, respectively. The major down-stream genes of VcFT, i.e., SUPPRESSOR of Overexpression of Constans 1-like (VcSOC1), LEAFY-like (VcLFY), APETALA1-like (VcAP1), CAULIFLOWER 1-like (VcCAL1), and FRUITFULL-like (VcFUL) genes were present and showed high similarity to their orthologues in herbaceous plants. Moreover, overexpression of VcFT promoted expression of all of these VcFT downstream genes. These results suggest that VcFT’s down-stream genes appear conserved in blueberry. PMID:27271296

Transcript Profile of Flowering Regulatory Genes in VcFT-Overexpressing Blueberry Plants.

PubMed

Walworth, Aaron E; Chai, Benli; Song, Guo-Qing

2016-01-01

In order to identify genetic components in flowering pathways of highbush blueberry (Vaccinium corymbosum L.), a transcriptome reference composed of 254,396 transcripts and 179,853 gene contigs was developed by assembly of 72.7 million reads using Trinity. Using this transcriptome reference and a query of flowering pathway genes of herbaceous plants, we identified potential flowering pathway genes/transcripts of blueberry. Transcriptome analysis of flowering pathway genes was then conducted on leaf tissue samples of transgenic blueberry cv. Aurora ('VcFT-Aurora'), which overexpresses a blueberry FLOWERING LOCUS T-like gene (VcFT). Sixty-one blueberry transcripts of 40 genes showed high similarities to 33 known flowering-related genes of herbaceous plants, of which 17 down-regulated and 16 up-regulated genes were identified in 'VcFT-Aurora'. All down-regulated genes encoded transcription factors/enzymes upstream in the signaling pathway containing VcFT. A blueberry CONSTANS-LIKE 5-like (VcCOL5) gene was down-regulated and associated with five other differentially expressed (DE) genes in the photoperiod-mediated flowering pathway. Three down-regulated genes, i.e., a MADS-AFFECTING FLOWERING 2-like gene (VcMAF2), a MADS-AFFECTING FLOWERING 5-like gene (VcMAF5), and a VERNALIZATION1-like gene (VcVRN1), may function as integrators in place of FLOWERING LOCUS C (FLC) in the vernalization pathway. Because no CONSTAN1-like or FLOWERING LOCUS C-like genes were found in blueberry, VcCOL5 and VcMAF2/VcMAF5 or VRN1 might be the major integrator(s) in the photoperiod- and vernalization-mediated flowering pathway, respectively. The major down-stream genes of VcFT, i.e., SUPPRESSOR of Overexpression of Constans 1-like (VcSOC1), LEAFY-like (VcLFY), APETALA1-like (VcAP1), CAULIFLOWER 1-like (VcCAL1), and FRUITFULL-like (VcFUL) genes were present and showed high similarity to their orthologues in herbaceous plants. Moreover, overexpression of VcFT promoted expression of all of these VcFT downstream genes. These results suggest that VcFT's down-stream genes appear conserved in blueberry.

Co-regulation of pluripotency and genetic integrity at the genomic level.

PubMed

Cooper, Daniel J; Walter, Christi A; McCarrey, John R

2014-11-01

The Disposable Soma Theory holds that genetic integrity will be maintained at more pristine levels in germ cells than in somatic cells because of the unique role germ cells play in perpetuating the species. We tested the hypothesis that the same concept applies to pluripotent cells compared to differentiated cells. Analyses of transcriptome and cistrome databases, along with canonical pathway analysis and chromatin immunoprecipitation confirmed differential expression of DNA repair and cell death genes in embryonic stem cells and induced pluripotent stem cells relative to fibroblasts, and predicted extensive direct and indirect interactions between the pluripotency and genetic integrity gene networks in pluripotent cells. These data suggest that enhanced maintenance of genetic integrity is fundamentally linked to the epigenetic state of pluripotency at the genomic level. In addition, these findings demonstrate how a small number of key pluripotency factors can regulate large numbers of downstream genes in a pathway-specific manner. Copyright © 2014. Published by Elsevier B.V.

Integrative Biological Analysis For Neuropsychopharmacology

PubMed Central

Emmett, Mark R; Kroes, Roger A; Moskal, Joseph R; Conrad, Charles A; Priebe, Waldemar; Laezza, Fernanda; Meyer-Baese, Anke; Nilsson, Carol L

2014-01-01

Although advances in psychotherapy have been made in recent years, drug discovery for brain diseases such as schizophrenia and mood disorders has stagnated. The need for new biomarkers and validated therapeutic targets in the field of neuropsychopharmacology is widely unmet. The brain is the most complex part of human anatomy from the standpoint of number and types of cells, their interconnections, and circuitry. To better meet patient needs, improved methods to approach brain studies by understanding functional networks that interact with the genome are being developed. The integrated biological approaches—proteomics, transcriptomics, metabolomics, and glycomics—have a strong record in several areas of biomedicine, including neurochemistry and neuro-oncology. Published applications of an integrated approach to projects of neurological, psychiatric, and pharmacological natures are still few but show promise to provide deep biological knowledge derived from cells, animal models, and clinical materials. Future studes that yield insights based on integrated analyses promise to deliver new therapeutic targets and biomarkers for personalized medicine. PMID:23800968

Transcriptome landscape of Synechococcus elongatus PCC 7942 for nitrogen starvation responses using RNA-seq

PubMed Central

Choi, Sun Young; Park, Byeonghyeok; Choi, In-Geol; Sim, Sang Jun; Lee, Sun-Mi; Um, Youngsoon; Woo, Han Min

2016-01-01

The development of high-throughput technology using RNA-seq has allowed understanding of cellular mechanisms and regulations of bacterial transcription. In addition, transcriptome analysis with RNA-seq has been used to accelerate strain improvement through systems metabolic engineering. Synechococcus elongatus PCC 7942, a photosynthetic bacterium, has remarkable potential for biochemical and biofuel production due to photoautotrophic cell growth and direct CO2 conversion. Here, we performed a transcriptome analysis of S. elongatus PCC 7942 using RNA-seq to understand the changes of cellular metabolism and regulation for nitrogen starvation responses. As a result, differentially expressed genes (DEGs) were identified and functionally categorized. With mapping onto metabolic pathways, we probed transcriptional perturbation and regulation of carbon and nitrogen metabolisms relating to nitrogen starvation responses. Experimental evidence such as chlorophyll a and phycobilisome content and the measurement of CO2 uptake rate validated the transcriptome analysis. The analysis suggests that S. elongatus PCC 7942 reacts to nitrogen starvation by not only rearranging the cellular transport capacity involved in carbon and nitrogen assimilation pathways but also by reducing protein synthesis and photosynthesis activities. PMID:27488818

Transcriptomics of cortical gray matter thickness decline during normal aging

PubMed Central

Kochunov, P; Charlesworth, J; Winkler, A; Hong, LE; Nichols, T; Curran, JE; Sprooten, E; Jahanshad, N; Thompson, PM; Johnson, MP; Kent, JW; Landman, BA; Mitchell, B; Cole, SA; Dyer, TD; Moses, EK; Goring, HHH; Almasy, L; Duggirala, R; Olvera, RL; Glahn, DC; Blangero, J

2013-01-01

Introduction We performed a whole-transcriptome correlation analysis, followed by the pathway enrichment and testing of innate immune response pathways analyses to evaluate the hypothesis that transcriptional activity can predict cortical gray matter thickness (GMT) variability during normal cerebral aging Methods Transcriptome and GMT data were availabe for 379 individuals (age range=28–85) community-dwelling members of large extended Mexican-American families. Collection of transcriptome data preceded that of neuroimaging data by 17 years. Genome-wide gene transcriptome data consisted of 20,413 heritable lymphocytes-based transcripts. GMT measurements were performed from high-resolution (isotropic 800µm) T1-weighted MRI. Transcriptome-wide and pathway enrichment analysis was used to classify genes correlated with GMT. Transcripts for sixty genes from seven innate immune pathways were tested as specific predictors of GMT variability. Results Transcripts for eight genes (IGFBP3, LRRN3, CRIP2, SCD, IDS, TCF4, GATA3, HN1) passed the transcriptome-wide significance threshold. Four orthogonal factors extracted from this set predicted 31.9% of the variability in the whole-brain and between 23.4 and 35% of regional GMT measurements. Pathway enrichment analysis identified six functional categories including cellular proliferation, aggregation, differentiation, viral infection, and metabolism. The integrin signaling pathway was significantly (p<10−6) enriched with GMT. Finally, three innate immune pathways (complement signaling, toll-receptors and scavenger and immunoglobulins) were significantly associated with GMT. Conclusion Expression activity for the genes that regulate cellular proliferation, adhesion, differentiation and inflammation can explain a significant proportion of individual variability in cortical GMT. Our findings suggest that normal cerebral aging is the product of a progressive decline in regenerative capacity and increased neuroinflammation. PMID:23707588

Transcriptomics of cortical gray matter thickness decline during normal aging.

PubMed

Kochunov, P; Charlesworth, J; Winkler, A; Hong, L E; Nichols, T E; Curran, J E; Sprooten, E; Jahanshad, N; Thompson, P M; Johnson, M P; Kent, J W; Landman, B A; Mitchell, B; Cole, S A; Dyer, T D; Moses, E K; Goring, H H H; Almasy, L; Duggirala, R; Olvera, R L; Glahn, D C; Blangero, J

2013-11-15

We performed a whole-transcriptome correlation analysis, followed by the pathway enrichment and testing of innate immune response pathway analyses to evaluate the hypothesis that transcriptional activity can predict cortical gray matter thickness (GMT) variability during normal cerebral aging. Transcriptome and GMT data were available for 379 individuals (age range=28-85) community-dwelling members of large extended Mexican American families. Collection of transcriptome data preceded that of neuroimaging data by 17 years. Genome-wide gene transcriptome data consisted of 20,413 heritable lymphocytes-based transcripts. GMT measurements were performed from high-resolution (isotropic 800 μm) T1-weighted MRI. Transcriptome-wide and pathway enrichment analysis was used to classify genes correlated with GMT. Transcripts for sixty genes from seven innate immune pathways were tested as specific predictors of GMT variability. Transcripts for eight genes (IGFBP3, LRRN3, CRIP2, SCD, IDS, TCF4, GATA3, and HN1) passed the transcriptome-wide significance threshold. Four orthogonal factors extracted from this set predicted 31.9% of the variability in the whole-brain and between 23.4 and 35% of regional GMT measurements. Pathway enrichment analysis identified six functional categories including cellular proliferation, aggregation, differentiation, viral infection, and metabolism. The integrin signaling pathway was significantly (p<10(-6)) enriched with GMT. Finally, three innate immune pathways (complement signaling, toll-receptors and scavenger and immunoglobulins) were significantly associated with GMT. Expression activity for the genes that regulate cellular proliferation, adhesion, differentiation and inflammation can explain a significant proportion of individual variability in cortical GMT. Our findings suggest that normal cerebral aging is the product of a progressive decline in regenerative capacity and increased neuroinflammation. Copyright © 2013 Elsevier Inc. All rights reserved.

The toxicological application of transcriptomics and epigenomics in zebrafish and other teleosts.

PubMed

Williams, Tim D; Mirbahai, Leda; Chipman, J Kevin

2014-03-01

Zebrafish (Danio rerio) is one of a number of teleost fish species frequently employed in toxicology. Toxico-genomics determines global transcriptomic responses to chemical exposures and can predict their effects. It has been applied successfully within aquatic toxicology to assist in chemical testing, determination of mechanisms and environmental monitoring. Moreover, the related field of toxico-epigenomics, that determines chemical-induced changes in DNA methylation, histone modifications and micro-RNA expression, is emerging as a valuable contribution to understanding mechanisms of both adaptive and adverse responses. Zebrafish has proven a useful and convenient model species for both transcriptomic and epigenetic toxicological studies. Despite zebrafish's dominance in other areas of fish biology, alternative fish species are used extensively in toxico-genomics. The main reason for this is that environmental monitoring generally focuses on species native to the region of interest. We are starting to see advances in the integration of high-throughput screening, omics techniques and bioinformatics together with more traditional indicator endpoints that are relevant to regulators. Integration of such approaches with high-throughput testing of zebrafish embryos, leading to the discovery of adverse outcome pathways, promises to make a major contribution to ensuring the safety of chemicals in the environment.

SRSF3 maintains transcriptome integrity in oocytes by regulation of alternative splicing and transposable elements.

PubMed

Do, Dang Vinh; Strauss, Bernhard; Cukuroglu, Engin; Macaulay, Iain; Wee, Keng Boon; Hu, Tim Xiaoming; Igor, Ruiz De Los Mozos; Lee, Caroline; Harrison, Andrew; Butler, Richard; Dietmann, Sabine; Jernej, Ule; Marioni, John; Smith, Christopher W J; Göke, Jonathan; Surani, M Azim

2018-01-01

The RNA-binding protein SRSF3 (also known as SRp20) has critical roles in the regulation of pre-mRNA splicing. Zygotic knockout of Srsf3 results in embryo arrest at the blastocyst stage. However, SRSF3 is also present in oocytes, suggesting that it might be critical as a maternally inherited factor. Here we identify SRSF3 as an essential regulator of alternative splicing and of transposable elements to maintain transcriptome integrity in mouse oocyte. Using 3D time-lapse confocal live imaging, we show that conditional deletion of Srsf3 in fully grown germinal vesicle oocytes substantially compromises the capacity of germinal vesicle breakdown (GVBD), and consequently entry into meiosis. By combining single cell RNA-seq, and oocyte micromanipulation with steric blocking antisense oligonucleotides and RNAse-H inducing gapmers, we found that the GVBD defect in mutant oocytes is due to both aberrant alternative splicing and derepression of B2 SINE transposable elements. Together, our study highlights how control of transcriptional identity of the maternal transcriptome by the RNA-binding protein SRSF3 is essential to the development of fertilized-competent oocytes.

Cell wall modifications of two Arabidopsis thaliana ecotypes, Col and Sha, in response to sub-optimal growth conditions: An integrative study.

PubMed

Duruflé, Harold; Hervé, Vincent; Ranocha, Philippe; Balliau, Thierry; Zivy, Michel; Chourré, Josiane; San Clemente, Hélène; Burlat, Vincent; Albenne, Cécile; Déjean, Sébastien; Jamet, Elisabeth; Dunand, Christophe

2017-10-01

With the global temperature change, plant adaptations are predicted, but little is known about the molecular mechanisms underlying them. Arabidopsis thaliana is a model plant adapted to various environmental conditions, in particular able to develop along an altitudinal gradient. Two ecotypes, Columbia (Col) growing at low altitude, and Shahdara (Sha) growing at 3400m, have been studied at optimal and sub-optimal growth temperature (22°C vs 15°C). Macro- and micro-phenotyping, cell wall monosaccharides analyses, cell wall proteomics, and transcriptomics have been performed in order to accomplish an integrative analysis. The analysis has been focused on cell walls (CWs) which are assumed to play roles in response to environmental changes. At 15°C, both ecotypes presented characteristic morphological traits of low temperature growth acclimation such as reduced rosette diameter, increased number of leaves, modifications of their CW composition and cuticle reinforcement. Altogether, the integrative analysis has allowed identifying several candidate genes/proteins possibly involved in the cell wall modifications observed during the temperature acclimation response. Copyright © 2017 Elsevier B.V. All rights reserved.

Integration of copy number and transcriptomics provides risk stratification in prostate cancer: A discovery and validation cohort study

PubMed Central

Ross-Adams, H.; Lamb, A.D.; Dunning, M.J.; Halim, S.; Lindberg, J.; Massie, C.M.; Egevad, L.A.; Russell, R.; Ramos-Montoya, A.; Vowler, S.L.; Sharma, N.L.; Kay, J.; Whitaker, H.; Clark, J.; Hurst, R.; Gnanapragasam, V.J.; Shah, N.C.; Warren, A.Y.; Cooper, C.S.; Lynch, A.G.; Stark, R.; Mills, I.G.; Grönberg, H.; Neal, D.E.

2015-01-01

Background Understanding the heterogeneous genotypes and phenotypes of prostate cancer is fundamental to improving the way we treat this disease. As yet, there are no validated descriptions of prostate cancer subgroups derived from integrated genomics linked with clinical outcome. Methods In a study of 482 tumour, benign and germline samples from 259 men with primary prostate cancer, we used integrative analysis of copy number alterations (CNA) and array transcriptomics to identify genomic loci that affect expression levels of mRNA in an expression quantitative trait loci (eQTL) approach, to stratify patients into subgroups that we then associated with future clinical behaviour, and compared with either CNA or transcriptomics alone. Findings We identified five separate patient subgroups with distinct genomic alterations and expression profiles based on 100 discriminating genes in our separate discovery and validation sets of 125 and 103 men. These subgroups were able to consistently predict biochemical relapse (p = 0.0017 and p = 0.016 respectively) and were further validated in a third cohort with long-term follow-up (p = 0.027). We show the relative contributions of gene expression and copy number data on phenotype, and demonstrate the improved power gained from integrative analyses. We confirm alterations in six genes previously associated with prostate cancer (MAP3K7, MELK, RCBTB2, ELAC2, TPD52, ZBTB4), and also identify 94 genes not previously linked to prostate cancer progression that would not have been detected using either transcript or copy number data alone. We confirm a number of previously published molecular changes associated with high risk disease, including MYC amplification, and NKX3-1, RB1 and PTEN deletions, as well as over-expression of PCA3 and AMACR, and loss of MSMB in tumour tissue. A subset of the 100 genes outperforms established clinical predictors of poor prognosis (PSA, Gleason score), as well as previously published gene signatures (p = 0.0001). We further show how our molecular profiles can be used for the early detection of aggressive cases in a clinical setting, and inform treatment decisions. Interpretation For the first time in prostate cancer this study demonstrates the importance of integrated genomic analyses incorporating both benign and tumour tissue data in identifying molecular alterations leading to the generation of robust gene sets that are predictive of clinical outcome in independent patient cohorts. PMID:26501111

Genetic signatures of adaptation revealed from transcriptome sequencing of Arctic and red foxes.

PubMed

Kumar, Vikas; Kutschera, Verena E; Nilsson, Maria A; Janke, Axel

2015-08-07

The genus Vulpes (true foxes) comprises numerous species that inhabit a wide range of habitats and climatic conditions, including one species, the Arctic fox (Vulpes lagopus) which is adapted to the arctic region. A close relative to the Arctic fox, the red fox (Vulpes vulpes), occurs in subarctic to subtropical habitats. To study the genetic basis of their adaptations to different environments, transcriptome sequences from two Arctic foxes and one red fox individual were generated and analyzed for signatures of positive selection. In addition, the data allowed for a phylogenetic analysis and divergence time estimate between the two fox species. The de novo assembly of reads resulted in more than 160,000 contigs/transcripts per individual. Approximately 17,000 homologous genes were identified using human and the non-redundant databases. Positive selection analyses revealed several genes involved in various metabolic and molecular processes such as energy metabolism, cardiac gene regulation, apoptosis and blood coagulation to be under positive selection in foxes. Branch site tests identified four genes to be under positive selection in the Arctic fox transcriptome, two of which are fat metabolism genes. In the red fox transcriptome eight genes are under positive selection, including molecular process genes, notably genes involved in ATP metabolism. Analysis of the three transcriptomes and five Sanger re-sequenced genes in additional individuals identified a lower genetic variability within Arctic foxes compared to red foxes, which is consistent with distribution range differences and demographic responses to past climatic fluctuations. A phylogenomic analysis estimated that the Arctic and red fox lineages diverged about three million years ago. Transcriptome data are an economic way to generate genomic resources for evolutionary studies. Despite not representing an entire genome, this transcriptome analysis identified numerous genes that are relevant to arctic adaptation in foxes. Similar to polar bears, fat metabolism seems to play a central role in adaptation of Arctic foxes to the cold climate, as has been identified in the polar bear, another arctic specialist.

DOGMA: domain-based transcriptome and proteome quality assessment.

PubMed

Dohmen, Elias; Kremer, Lukas P M; Bornberg-Bauer, Erich; Kemena, Carsten

2016-09-01

Genome studies have become cheaper and easier than ever before, due to the decreased costs of high-throughput sequencing and the free availability of analysis software. However, the quality of genome or transcriptome assemblies can vary a lot. Therefore, quality assessment of assemblies and annotations are crucial aspects of genome analysis pipelines. We developed DOGMA, a program for fast and easy quality assessment of transcriptome and proteome data based on conserved protein domains. DOGMA measures the completeness of a given transcriptome or proteome and provides information about domain content for further analysis. DOGMA provides a very fast way to do quality assessment within seconds. DOGMA is implemented in Python and published under GNU GPL v.3 license. The source code is available on https://ebbgit.uni-muenster.de/domainWorld/DOGMA/ CONTACTS: e.dohmen@wwu.de or c.kemena@wwu.de Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Integration of genomic, transcriptomic and proteomic data identifies two biologically distinct subtypes of invasive lobular breast cancer

PubMed Central

Michaut, Magali; Chin, Suet-Feung; Majewski, Ian; Severson, Tesa M.; Bismeijer, Tycho; de Koning, Leanne; Peeters, Justine K.; Schouten, Philip C.; Rueda, Oscar M.; Bosma, Astrid J.; Tarrant, Finbarr; Fan, Yue; He, Beilei; Xue, Zheng; Mittempergher, Lorenza; Kluin, Roelof J.C.; Heijmans, Jeroen; Snel, Mireille; Pereira, Bernard; Schlicker, Andreas; Provenzano, Elena; Ali, Hamid Raza; Gaber, Alexander; O’Hurley, Gillian; Lehn, Sophie; Muris, Jettie J.F.; Wesseling, Jelle; Kay, Elaine; Sammut, Stephen John; Bardwell, Helen A.; Barbet, Aurélie S.; Bard, Floriane; Lecerf, Caroline; O’Connor, Darran P.; Vis, Daniël J.; Benes, Cyril H.; McDermott, Ultan; Garnett, Mathew J.; Simon, Iris M.; Jirström, Karin; Dubois, Thierry; Linn, Sabine C.; Gallagher, William M.; Wessels, Lodewyk F.A.; Caldas, Carlos; Bernards, Rene

2016-01-01

Invasive lobular carcinoma (ILC) is the second most frequently occurring histological breast cancer subtype after invasive ductal carcinoma (IDC), accounting for around 10% of all breast cancers. The molecular processes that drive the development of ILC are still largely unknown. We have performed a comprehensive genomic, transcriptomic and proteomic analysis of a large ILC patient cohort and present here an integrated molecular portrait of ILC. Mutations in CDH1 and in the PI3K pathway are the most frequent molecular alterations in ILC. We identified two main subtypes of ILCs: (i) an immune related subtype with mRNA up-regulation of PD-L1, PD-1 and CTLA-4 and greater sensitivity to DNA-damaging agents in representative cell line models; (ii) a hormone related subtype, associated with Epithelial to Mesenchymal Transition (EMT), and gain of chromosomes 1q and 8q and loss of chromosome 11q. Using the somatic mutation rate and eIF4B protein level, we identified three groups with different clinical outcomes, including a group with extremely good prognosis. We provide a comprehensive overview of the molecular alterations driving ILC and have explored links with therapy response. This molecular characterization may help to tailor treatment of ILC through the application of specific targeted, chemo- and/or immune-therapies. PMID:26729235

A-WINGS: an integrated genome database for Pleurocybella porrigens (Angel's wing oyster mushroom, Sugihiratake).

PubMed

Yamamoto, Naoki; Suzuki, Tomohiro; Kobayashi, Masaaki; Dohra, Hideo; Sasaki, Yohei; Hirai, Hirofumi; Yokoyama, Koji; Kawagishi, Hirokazu; Yano, Kentaro

2014-12-03

The angel's wing oyster mushroom (Pleurocybella porrigens, Sugihiratake) is a well-known delicacy. However, its potential risk in acute encephalopathy was recently revealed by a food poisoning incident. To disclose the genes underlying the accident and provide mechanistic insight, we seek to develop an information infrastructure containing omics data. In our previous work, we sequenced the genome and transcriptome using next-generation sequencing techniques. The next step in achieving our goal is to develop a web database to facilitate the efficient mining of large-scale omics data and identification of genes specifically expressed in the mushroom. This paper introduces a web database A-WINGS (http://bioinf.mind.meiji.ac.jp/a-wings/) that provides integrated genomic and transcriptomic information for the angel's wing oyster mushroom. The database contains structure and functional annotations of transcripts and gene expressions. Functional annotations contain information on homologous sequences from NCBI nr and UniProt, Gene Ontology, and KEGG Orthology. Digital gene expression profiles were derived from RNA sequencing (RNA-seq) analysis in the fruiting bodies and mycelia. The omics information stored in the database is freely accessible through interactive and graphical interfaces by search functions that include 'GO TREE VIEW' browsing, keyword searches, and BLAST searches. The A-WINGS database will accelerate omics studies on specific aspects of the angel's wing oyster mushroom and the family Tricholomataceae.

A systemic identification approach for primary transcription start site of Arabidopsis miRNAs from multidimensional omics data.

PubMed

You, Qi; Yan, Hengyu; Liu, Yue; Yi, Xin; Zhang, Kang; Xu, Wenying; Su, Zhen

2017-05-01

The 22-nucleotide non-coding microRNAs (miRNAs) are mostly transcribed by RNA polymerase II and are similar to protein-coding genes. Unlike the clear process from stem-loop precursors to mature miRNAs, the primary transcriptional regulation of miRNA, especially in plants, still needs to be further clarified, including the original transcription start site, functional cis-elements and primary transcript structures. Due to several well-characterized transcription signals in the promoter region, we proposed a systemic approach integrating multidimensional "omics" (including genomics, transcriptomics, and epigenomics) data to improve the genome-wide identification of primary miRNA transcripts. Here, we used the model plant Arabidopsis thaliana to improve the ability to identify candidate promoter locations in intergenic miRNAs and to determine rules for identifying primary transcription start sites of miRNAs by integrating high-throughput omics data, such as the DNase I hypersensitive sites, chromatin immunoprecipitation-sequencing of polymerase II and H3K4me3, as well as high throughput transcriptomic data. As a result, 93% of refined primary transcripts could be confirmed by the primer pairs from a previous study. Cis-element and secondary structure analyses also supported the feasibility of our results. This work will contribute to the primary transcriptional regulatory analysis of miRNAs, and the conserved regulatory pattern may be a suitable miRNA characteristic in other plant species.

Integrated analysis of phenome, genome, and transcriptome of hybrid rice uncovered multiple heterosis-related loci for yield increase

PubMed Central

Li, Dayong; Huang, Zhiyuan; Song, Shuhui; Xin, Yeyun; Mao, Donghai; Lv, Qiming; Zhou, Ming; Tian, Dongmei; Tang, Mingfeng; Wu, Qi; Liu, Xue; Chen, Tingting; Song, Xianwei; Fu, Xiqin; Zhao, Bingran; Liang, Chengzhi; Li, Aihong; Liu, Guozhen; Li, Shigui; Hu, Songnian; Cao, Xiaofeng; Yu, Jun; Yuan, Longping; Chen, Caiyan; Zhu, Lihuang

2016-01-01

Hybrid rice is the dominant form of rice planted in China, and its use has extended worldwide since the 1970s. It offers great yield advantages and has contributed greatly to the world’s food security. However, the molecular mechanisms underlying heterosis have remained a mystery. In this study we integrated genetics and omics analyses to determine the candidate genes for yield heterosis in a model two-line rice hybrid system, Liang-you-pei 9 (LYP9) and its parents. Phenomics study revealed that the better parent heterosis (BPH) of yield in hybrid is not ascribed to BPH of all the yield components but is specific to the BPH of spikelet number per panicle (SPP) and paternal parent heterosis (PPH) of effective panicle number (EPN). Genetic analyses then identified multiple quantitative trait loci (QTLs) for these two components. Moreover, a number of differentially expressed genes and alleles in the hybrid were mapped by transcriptome profiling to the QTL regions as possible candidate genes. In parallel, a major QTL for yield heterosis, rice heterosis 8 (RH8), was found to be the DTH8/Ghd8/LHD1 gene. Based on the shared allelic heterozygosity of RH8 in many hybrid rice cultivars, a common mechanism for yield heterosis in the present commercial hybrid rice is proposed. PMID:27663737

Transcriptomic analysis of submergence-tolerant and sensitive Brachypodium distachyon ecotypes reveals oxidative stress as a major tolerance factor

PubMed Central

Rivera-Contreras, Irma Karla; Zamora-Hernández, Teresa; Huerta-Heredia, Ariana Arlene; Capataz-Tafur, Jacqueline; Barrera-Figueroa, Blanca Estela; Juntawong, Piyada; Peña-Castro, Julián Mario

2016-01-01

When excessive amounts of water accumulate around roots and aerial parts of plants, submergence stress occurs. To find the integrated mechanisms of tolerance, we used ecotypes of the monocot model plant Brachypodium distachyon to screen for genetic material with contrasting submergence tolerance. For this purpose, we used a set of previously studied drought sensitive/tolerant ecotypes and the knowledge that drought tolerance is positively associated with submergence stress. We decided to contrast aerial tissue transcriptomes of the ecotype Bd21 14-day-old plants as sensitive and ecotype Bd2-3 as tolerant after 2 days of stress under a long-day photoperiod. Gene ontology and the grouping of transcripts indicated that tolerant Bd2-3 differentially down-regulated NITRATE REDUCTASE and ALTERNATIVE OXIDASE under stress and constitutively up-regulated HAEMOGLOBIN, when compared with the sensitive ecotype, Bd21. These results suggested the removal of nitric oxide, a gaseous phytohormone and concomitant reactive oxygen species as a relevant tolerance determinant. Other mechanisms more active in tolerant Bd2-3 were the pathogen response, glyoxylate and tricarboxylic acid cycle integration, and acetate metabolism. This data set could be employed to design further studies on the basic science of plant tolerance to submergence stress and its biotechnological application in the development of submergence-tolerant crops. PMID:27282694

Integrative approaches for large-scale transcriptome-wide association studies

PubMed Central

Gusev, Alexander; Ko, Arthur; Shi, Huwenbo; Bhatia, Gaurav; Chung, Wonil; Penninx, Brenda W J H; Jansen, Rick; de Geus, Eco JC; Boomsma, Dorret I; Wright, Fred A; Sullivan, Patrick F; Nikkola, Elina; Alvarez, Marcus; Civelek, Mete; Lusis, Aldons J.; Lehtimäki, Terho; Raitoharju, Emma; Kähönen, Mika; Seppälä, Ilkka; Raitakari, Olli T.; Kuusisto, Johanna; Laakso, Markku; Price, Alkes L.; Pajukanta, Päivi; Pasaniuc, Bogdan

2016-01-01

Many genetic variants influence complex traits by modulating gene expression, thus altering the abundance levels of one or multiple proteins. Here, we introduce a powerful strategy that integrates gene expression measurements with summary association statistics from large-scale genome-wide association studies (GWAS) to identify genes whose cis-regulated expression is associated to complex traits. We leverage expression imputation to perform a transcriptome wide association scan (TWAS) to identify significant expression-trait associations. We applied our approaches to expression data from blood and adipose tissue measured in ~3,000 individuals overall. We imputed gene expression into GWAS data from over 900,000 phenotype measurements to identify 69 novel genes significantly associated to obesity-related traits (BMI, lipids, and height). Many of the novel genes are associated with relevant phenotypes in the Hybrid Mouse Diversity Panel. Our results showcase the power of integrating genotype, gene expression and phenotype to gain insights into the genetic basis of complex traits. PMID:26854917

Nuclear factor-kappaB bioluminescence imaging-guided transcriptomic analysis for the assessment of host-biomaterial interaction in vivo.

PubMed

Hsiang, Chien-Yun; Chen, Yueh-Sheng; Ho, Tin-Yun

2009-06-01

Establishment of a comprehensive platform for the assessment of host-biomaterial interaction in vivo is an important issue. Nuclear factor-kappaB (NF-kappaB) is an inducible transcription factor that is activated by numerous stimuli. Therefore, NF-kappaB-dependent luminescent signal in transgenic mice carrying the luciferase genes was used as the guide to monitor the biomaterials-affected organs, and transcriptomic analysis was further applied to evaluate the complex host responses in affected organs in this study. In vivo imaging showed that genipin-cross-linked gelatin conduit (GGC) implantation evoked the strong NF-kappaB activity at 6h in the implanted region, and transcriptomic analysis showed that the expressions of interleukin-6 (IL-6), IL-24, and IL-1 family were up-regulated. A strong luminescent signal was observed in spleen on 14 d, suggesting that GGC implantation might elicit the biological events in spleen. Transcriptomic analysis of spleen showed that 13 Kyoto Encyclopedia of Genes and Genomes pathways belonging to cell cycles, immune responses, and metabolism were significantly altered by GGC implants. Connectivity Map analysis suggested that the gene signatures of GGC were similar to those of compounds that affect lipid or glucose metabolism. GeneSetTest analysis further showed that host responses to GGC implants might be related to diseases states, especially the metabolic and cardiovascular diseases. In conclusion, our data provided a concept of molecular imaging-guided transcriptomic platform for the evaluation and the prediction of host-biomaterial interaction in vivo.

Early molecular events involved in Pinus pinaster Ait. somatic embryo development under reduced water availability: transcriptomic and proteomic analyses.

PubMed

Morel, Alexandre; Teyssier, Caroline; Trontin, Jean-François; Eliášová, Kateřina; Pešek, Bedřich; Beaufour, Martine; Morabito, Domenico; Boizot, Nathalie; Le Metté, Claire; Belal-Bessai, Leila; Reymond, Isabelle; Harvengt, Luc; Cadene, Martine; Corbineau, Françoise; Vágner, Martin; Label, Philippe; Lelu-Walter, Marie-Anne

2014-09-01

Maritime pine somatic embryos (SEs) require a reduction in water availability (high gellan gum concentration in the maturation medium) to reach the cotyledonary stage. This key switch, reported specifically for pine species, is not yet well understood. To facilitate the use of somatic embryogenesis for mass propagation of conifers, we need a better understanding of embryo development. Comparison of both transcriptome (Illumina RNA sequencing) and proteome [two-dimensional sodium dodecyl sulfate-polyacrylamide gel electrophoresis with mass spectrometry (MS) identification] of immature SEs, cultured on either high (9G) or low (4G) gellan gum concentration, was performed, together with analysis of water content, fresh and dry mass, endogenous abscisic acid (ABA; gas chromatography-MS), soluble sugars (high-pressure liquid chromatography), starch and confocal laser microscope observations. This multiscale, integrated analysis was used to unravel early molecular and physiological events involved in SE development. Under unfavorable conditions (4G), the glycolytic pathway was enhanced, possibly in relation to cell proliferation that may be antagonistic to SE development. Under favorable conditions (9G), SEs adapted to culture constraint by activating specific protective pathways, and ABA-mediated molecular and physiological responses promoting embryo development. Our results suggest that on 9G, germin-like protein and ubiquitin-protein ligase could be used as predictive markers of SE development, whereas protein phosphatase 2C could be a biomarker for culture adaptive responses. This is the first characterization of early molecular mechanisms involved in the development of pine SEs following an increase in gellan gum concentration in the maturation medium, and it is also the first report on somatic embryogenesis in conifers combining transcriptomic and proteomic datasets. © 2014 Scandinavian Plant Physiology Society.

Systems Biology Analysis of Zymomonas mobilis ZM4 Ethanol Stress Responses

PubMed Central

Yang, Shihui; Pan, Chongle; Tschaplinski, Timothy J.; Hurst, Gregory B.; Engle, Nancy L.; Zhou, Wen; Dam, PhuongAn; Xu, Ying; Rodriguez, Miguel; Dice, Lezlee; Johnson, Courtney M.; Davison, Brian H.; Brown, Steven D.

2013-01-01

Background Zymomonas mobilis ZM4 is a capable ethanologenic bacterium with high ethanol productivity and ethanol tolerance. Previous studies indicated that several stress-related proteins and changes in the ZM4 membrane lipid composition may contribute to ethanol tolerance. However, the molecular mechanisms of its ethanol stress response have not been elucidated fully. Methodology/Principal Findings In this study, ethanol stress responses were investigated using systems biology approaches. Medium supplementation with an initial 47 g/L (6% v/v) ethanol reduced Z. mobilis ZM4 glucose consumption, growth rate and ethanol productivity compared to that of untreated controls. A proteomic analysis of early exponential growth identified about one thousand proteins, or approximately 55% of the predicted ZM4 proteome. Proteins related to metabolism and stress response such as chaperones and key regulators were more abundant in the early ethanol stress condition. Transcriptomic studies indicated that the response of ZM4 to ethanol is dynamic, complex and involves many genes from all the different functional categories. Most down-regulated genes were related to translation and ribosome biogenesis, while the ethanol-upregulated genes were mostly related to cellular processes and metabolism. Transcriptomic data were used to update Z. mobilis ZM4 operon models. Furthermore, correlations among the transcriptomic, proteomic and metabolic data were examined. Among significantly expressed genes or proteins, we observe higher correlation coefficients when fold-change values are higher. Conclusions Our study has provided insights into the responses of Z. mobilis to ethanol stress through an integrated “omics” approach for the first time. This systems biology study elucidated key Z. mobilis ZM4 metabolites, genes and proteins that form the foundation of its distinctive physiology and its multifaceted response to ethanol stress. PMID:23874800

ONCOGENIC DRIVER GENES AND THE INFLAMMATORY MICROENVIRONMENT DICTATE LIVER TUMOR PHENOTYPE

PubMed Central

Matter, Matthias S.; Marquardt, Jens U.; Andersen, Jesper B.; Quintavalle, Cristina; Korokhov, Nikolay; Stauffer, Jim K.; Kaji, Kosuke; Decaens, Thomas; Quagliata, Luca; Elloumi, Fathi; Hoang, Tanya; Molinolo, Alfredo; Conner, Elizabeth A.; Weber, Achim; Heikenwalder, Mathias; Factor, Valentina M.; Thorgeirsson, Snorri S.

2016-01-01

The majority of hepatocellular carcinoma (HCC) develops in the background of chronic liver inflammation caused by viral hepatitis and alcoholic or non-alcoholic steatohepatitis. However, the impact of different types of chronic inflammatory microenvironments on the phenotypes of tumors generated by distinct oncogenes is largely unresolved. To address this issue, we generated murine liver tumors by constitutively active AKT-1 (AKT) and β-catenin (CAT) followed by induction of chronic liver inflammation by 3,5-diethoxycarbonyl-1,4-dihydrocollidine (DDC) and carbon tetrachloride (CCl4). Also, the impact of DDC-induced chronic liver inflammation was compared between two liver tumor models using a combination of AKT-CAT or AKT-NRASG12V. Treatment with DDC and CCl4 significantly facilitated the adenoma-to-carcinoma conversion and accelerated the growth of AKT-CAT tumors. Furthermore, DDC treatment altered the morphology of AKT-CAT tumors and caused loss of lipid droplets. Transcriptome analysis of AKT-CAT tumors revealed that cellular growth and proliferation was mainly affected by chronic inflammation and caused upregulated of Cxcl16, Galectin-3 and Nedd9 among others. Integration with transcriptome profiles from human HCCs further demonstrated that AKT-CAT tumors generated in the context of chronic liver inflammation showed enrichment of poor prognosis gene sets or decrease of good prognosis gene sets. In contrast, DDC had a more subtle effect on AKT-NRASG12V tumors and primarily enhanced already existent tumor characteristics as supported by transcriptome analysis. However, it also reduced lipid droplets in AKT-NRASG12V tumors. Conclusion Our study suggests that liver tumor phenotype is defined by a combination of driving oncogenes but also the nature of chronic liver inflammation. PMID:26844528

Genome and transcriptome sequencing in prospective metastatic triple-negative breast cancer uncovers therapeutic vulnerabilities.

PubMed

Craig, David W; O'Shaughnessy, Joyce A; Kiefer, Jeffrey A; Aldrich, Jessica; Sinari, Shripad; Moses, Tracy M; Wong, Shukmei; Dinh, Jennifer; Christoforides, Alexis; Blum, Joanne L; Aitelli, Cristi L; Osborne, Cynthia R; Izatt, Tyler; Kurdoglu, Ahmet; Baker, Angela; Koeman, Julie; Barbacioru, Catalin; Sakarya, Onur; De La Vega, Francisco M; Siddiqui, Asim; Hoang, Linh; Billings, Paul R; Salhia, Bodour; Tolcher, Anthony W; Trent, Jeffrey M; Mousses, Spyro; Von Hoff, Daniel; Carpten, John D

2013-01-01

Triple-negative breast cancer (TNBC) is characterized by the absence of expression of estrogen receptor, progesterone receptor, and HER-2. Thirty percent of patients recur after first-line treatment, and metastatic TNBC (mTNBC) has a poor prognosis with median survival of one year. Here, we present initial analyses of whole genome and transcriptome sequencing data from 14 prospective mTNBC. We have cataloged the collection of somatic genomic alterations in these advanced tumors, particularly those that may inform targeted therapies. Genes mutated in multiple tumors included TP53, LRP1B, HERC1, CDH5, RB1, and NF1. Notable genes involved in focal structural events were CTNNA1, PTEN, FBXW7, BRCA2, WT1, FGFR1, KRAS, HRAS, ARAF, BRAF, and PGCP. Homozygous deletion of CTNNA1 was detected in 2 of 6 African Americans. RNA sequencing revealed consistent overexpression of the FOXM1 gene when tumor gene expression was compared with nonmalignant breast samples. Using an outlier analysis of gene expression comparing one cancer with all the others, we detected expression patterns unique to each patient's tumor. Integrative DNA/RNA analysis provided evidence for deregulation of mutated genes, including the monoallelic expression of TP53 mutations. Finally, molecular alterations in several cancers supported targeted therapeutic intervention on clinical trials with known inhibitors, particularly for alterations in the RAS/RAF/MEK/ERK and PI3K/AKT/mTOR pathways. In conclusion, whole genome and transcriptome profiling of mTNBC have provided insights into somatic events occurring in this difficult to treat cancer. These genomic data have guided patients to investigational treatment trials and provide hypotheses for future trials in this irremediable cancer.

Cell-type- and tissue-specific transcriptomes of the white spruce (Picea glauca) bark unmask fine-scale spatial patterns of constitutive and induced conifer defense.

PubMed

Celedon, Jose M; Yuen, Macaire M S; Chiang, Angela; Henderson, Hannah; Reid, Karen E; Bohlmann, Jörg

2017-11-01

Plant defenses often involve specialized cells and tissues. In conifers, specialized cells of the bark are important for defense against insects and pathogens. Using laser microdissection, we characterized the transcriptomes of cortical resin duct cells, phenolic cells and phloem of white spruce (Picea glauca) bark under constitutive and methyl jasmonate (MeJa)-induced conditions, and we compared these transcriptomes with the transcriptome of the bark tissue complex. Overall, ~3700 bark transcripts were differentially expressed in response to MeJa. Approximately 25% of transcripts were expressed in only one cell type, revealing cell specialization at the transcriptome level. MeJa caused cell-type-specific transcriptome responses and changed the overall patterns of cell-type-specific transcript accumulation. Comparison of transcriptomes of the conifer bark tissue complex and specialized cells resolved a masking effect inherent to transcriptome analysis of complex tissues, and showed the actual cell-type-specific transcriptome signatures. Characterization of cell-type-specific transcriptomes is critical to reveal the dynamic patterns of spatial and temporal display of constitutive and induced defense systems in a complex plant tissue or organ. This was demonstrated with the improved resolution of spatially restricted expression of sets of genes of secondary metabolism in the specialized cell types. © 2017 The Authors The Plant Journal published by John Wiley & Sons Ltd and Society for Experimental Biology.

Transcriptome analysis and gene expression profiling of abortive and developing ovules during fruit development in hazelnut.

PubMed

Cheng, Yunqing; Liu, Jianfeng; Zhang, Huidi; Wang, Ju; Zhao, Yixin; Geng, Wanting

2015-01-01

A high ratio of blank fruit in hazelnut (Corylus heterophylla Fisch) is a very common phenomenon that causes serious yield losses in northeast China. The development of blank fruit in the Corylus genus is known to be associated with embryo abortion. However, little is known about the molecular mechanisms responsible for embryo abortion during the nut development stage. Genomic information for C. heterophylla Fisch is not available; therefore, data related to transcriptome and gene expression profiling of developing and abortive ovules are needed. In this study, de novo transcriptome sequencing and RNA-seq analysis were conducted using short-read sequencing technology (Illumina HiSeq 2000). The results of the transcriptome assembly analysis revealed genetic information that was associated with the fruit development stage. Two digital gene expression libraries were constructed, one for a full (normally developing) ovule and one for an empty (abortive) ovule. Transcriptome sequencing and assembly results revealed 55,353 unigenes, including 18,751 clusters and 36,602 singletons. These results were annotated using the public databases NR, NT, Swiss-Prot, KEGG, COG, and GO. Using digital gene expression profiling, gene expression differences in developing and abortive ovules were identified. A total of 1,637 and 715 unigenes were significantly upregulated and downregulated, respectively, in abortive ovules, compared with developing ovules. Quantitative real-time polymerase chain reaction analysis was used in order to verify the differential expression of some genes. The transcriptome and digital gene expression profiling data of normally developing and abortive ovules in hazelnut provide exhaustive information that will improve our understanding of the molecular mechanisms of abortive ovule formation in hazelnut.

Transcriptome Network Analysis Reveals Aging-Related Mitochondrial and Proteasomal Dysfunction and Immune Activation in Human Thyroid

PubMed Central

Cho, Byuri Angela; Yoo, Seong-Keun; Song, Young Shin; Kim, Su-jin; Lee, Kyu Eun; Shong, Minho

2018-01-01

Background: Elucidating aging-related transcriptomic changes in human organs is necessary to understand the aging physiology and mechanisms, but little is known regarding the thyroid gland. We investigated aging-related transcriptomic alterations in the human thyroid gland and characterized the related molecular functions. Methods: Publicly available RNA sequencing data of 322 thyroid tissue samples from the Genotype-Tissue Expression project were analyzed. In addition, our own 64 RNA sequencing data of normal thyroid tissue samples were used as a validation set. To comprehensively evaluate the associations between aging and transcriptomic changes, we performed a weighted gene coexpression network analysis and pathway enrichment analysis. The thyroid differentiation score was then used for further analysis, defining the correlations between thyroid differentiation and aging. Results: The most significant aging-related transcriptomic change in thyroid was the downregulation of genes related to the mitochondrial and proteasomal functions (p = 3 × 10−6). Moreover, genes that are associated with immune processes were significantly upregulated with age (p = 3 × 10−4), and all of them overlapped with the upregulated genes in the thyroid glands affected by lymphocytic thyroiditis. Furthermore, these aging-related changes were not significantly different according to sex, but in terms of the thyroid differentiation, females were more susceptible to aging-related changes (p for trend = 0.03). Conclusions: Aging-related transcriptomic changes in the thyroid gland were associated with mitochondrial and proteasomal dysfunction, loss of differentiation, and activation of autoimmune processes. Our results provide clues to better understanding the age-related decline in thyroid function and higher susceptibility to autoimmune thyroid disease. PMID:29652618

Impact of Transcriptomics on Our Understanding of Pulmonary Fibrosis

PubMed Central

Vukmirovic, Milica; Kaminski, Naftali

2018-01-01

Idiopathic pulmonary fibrosis (IPF) is a lethal fibrotic lung disease characterized by aberrant remodeling of the lung parenchyma with extensive changes to the phenotypes of all lung resident cells. The introduction of transcriptomics, genome scale profiling of thousands of RNA transcripts, caused a significant inversion in IPF research. Instead of generating hypotheses based on animal models of disease, or biological plausibility, with limited validation in humans, investigators were able to generate hypotheses based on unbiased molecular analysis of human samples and then use animal models of disease to test their hypotheses. In this review, we describe the insights made from transcriptomic analysis of human IPF samples. We describe how transcriptomic studies led to identification of novel genes and pathways involved in the human IPF lung such as: matrix metalloproteinases, WNT pathway, epithelial genes, role of microRNAs among others, as well as conceptual insights such as the involvement of developmental pathways and deep shifts in epithelial and fibroblast phenotypes. The impact of lung and transcriptomic studies on disease classification, endotype discovery, and reproducible biomarkers is also described in detail. Despite these impressive achievements, the impact of transcriptomic studies has been limited because they analyzed bulk tissue and did not address the cellular and spatial heterogeneity of the IPF lung. We discuss new emerging technologies and applications, such as single-cell RNAseq and microenvironment analysis that may address cellular and spatial heterogeneity. We end by making the point that most current tissue collections and resources are not amenable to analysis using the novel technologies. To take advantage of the new opportunities, we need new efforts of sample collections, this time focused on access to all the microenvironments and cells in the IPF lung. PMID:29670881

Integration of somatic mutation, expression and functional data reveals potential driver genes predictive of breast cancer survival.

PubMed

Suo, Chen; Hrydziuszko, Olga; Lee, Donghwan; Pramana, Setia; Saputra, Dhany; Joshi, Himanshu; Calza, Stefano; Pawitan, Yudi

2015-08-15

Genome and transcriptome analyses can be used to explore cancers comprehensively, and it is increasingly common to have multiple omics data measured from each individual. Furthermore, there are rich functional data such as predicted impact of mutations on protein coding and gene/protein networks. However, integration of the complex information across the different omics and functional data is still challenging. Clinical validation, particularly based on patient outcomes such as survival, is important for assessing the relevance of the integrated information and for comparing different procedures. An analysis pipeline is built for integrating genomic and transcriptomic alterations from whole-exome and RNA sequence data and functional data from protein function prediction and gene interaction networks. The method accumulates evidence for the functional implications of mutated potential driver genes found within and across patients. A driver-gene score (DGscore) is developed to capture the cumulative effect of such genes. To contribute to the score, a gene has to be frequently mutated, with high or moderate mutational impact at protein level, exhibiting an extreme expression and functionally linked to many differentially expressed neighbors in the functional gene network. The pipeline is applied to 60 matched tumor and normal samples of the same patient from The Cancer Genome Atlas breast-cancer project. In clinical validation, patients with high DGscores have worse survival than those with low scores (P = 0.001). Furthermore, the DGscore outperforms the established expression-based signatures MammaPrint and PAM50 in predicting patient survival. In conclusion, integration of mutation, expression and functional data allows identification of clinically relevant potential driver genes in cancer. The documented pipeline including annotated sample scripts can be found in http://fafner.meb.ki.se/biostatwiki/driver-genes/. yudi.pawitan@ki.se Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Understanding developmental and adaptive cues in pine through metabolite profiling and co-expression network analysis

PubMed Central

Cañas, Rafael A.; Canales, Javier; Muñoz-Hernández, Carmen; Granados, Jose M.; Ávila, Concepción; García-Martín, María L.; Cánovas, Francisco M.

2015-01-01

Conifers include long-lived evergreen trees of great economic and ecological importance, including pines and spruces. During their long lives conifers must respond to seasonal environmental changes, adapt to unpredictable environmental stresses, and co-ordinate their adaptive adjustments with internal developmental programmes. To gain insights into these responses, we examined metabolite and transcriptomic profiles of needles from naturally growing 25-year-old maritime pine (Pinus pinaster L. Aiton) trees over a year. The effect of environmental parameters such as temperature and rain on needle development were studied. Our results show that seasonal changes in the metabolite profiles were mainly affected by the needles’ age and acclimation for winter, but changes in transcript profiles were mainly dependent on climatic factors. The relative abundance of most transcripts correlated well with temperature, particularly for genes involved in photosynthesis or winter acclimation. Gene network analysis revealed relationships between 14 co-expressed gene modules and development and adaptation to environmental stimuli. Novel Myb transcription factors were identified as candidate regulators during needle development. Our systems-based analysis provides integrated data of the seasonal regulation of maritime pine growth, opening new perspectives for understanding the complex regulatory mechanisms underlying conifers’ adaptive responses. Taken together, our results suggest that the environment regulates the transcriptome for fine tuning of the metabolome during development. PMID:25873654

Reconstruction of the Fatty Acid Biosynthetic Pathway of Exiguobacterium antarcticum B7 Based on Genomic and Bibliomic Data

PubMed Central

Kawasaki, Regiane; Carepo, Marta S. P.; Oliveira, Rui; Marques, Rodolfo; Ramos, Rommel T. J.; Schneider, Maria P. C.

2016-01-01

Exiguobacterium antarcticum B7 is extremophile Gram-positive bacteria able to survive in cold environments. A key factor to understanding cold adaptation processes is related to the modification of fatty acids composing the cell membranes of psychrotrophic bacteria. In our study we show the in silico reconstruction of the fatty acid biosynthesis pathway of E. antarcticum B7. To build the stoichiometric model, a semiautomatic procedure was applied, which integrates genome information using KEGG and RAST/SEED. Constraint-based methods, namely, Flux Balance Analysis (FBA) and elementary modes (EM), were applied. FBA was implemented in the sense of hexadecenoic acid production maximization. To evaluate the influence of the gene expression in the fluxome analysis, FBA was also calculated using the log2⁡FC values obtained in the transcriptome analysis at 0°C and 37°C. The fatty acid biosynthesis pathway showed a total of 13 elementary flux modes, four of which showed routes for the production of hexadecenoic acid. The reconstructed pathway demonstrated the capacity of E. antarcticum B7 to de novo produce fatty acid molecules. Under the influence of the transcriptome, the fluxome was altered, promoting the production of short-chain fatty acids. The calculated models contribute to better understanding of the bacterial adaptation at cold environments. PMID:27595107

Epigenetic transgenerational inheritance of somatic transcriptomes and epigenetic control regions

PubMed Central

2012-01-01

Background Environmentally induced epigenetic transgenerational inheritance of adult onset disease involves a variety of phenotypic changes, suggesting a general alteration in genome activity. Results Investigation of different tissue transcriptomes in male and female F3 generation vinclozolin versus control lineage rats demonstrated all tissues examined had transgenerational transcriptomes. The microarrays from 11 different tissues were compared with a gene bionetwork analysis. Although each tissue transgenerational transcriptome was unique, common cellular pathways and processes were identified between the tissues. A cluster analysis identified gene modules with coordinated gene expression and each had unique gene networks regulating tissue-specific gene expression and function. A large number of statistically significant over-represented clusters of genes were identified in the genome for both males and females. These gene clusters ranged from 2-5 megabases in size, and a number of them corresponded to the epimutations previously identified in sperm that transmit the epigenetic transgenerational inheritance of disease phenotypes. Conclusions Combined observations demonstrate that all tissues derived from the epigenetically altered germ line develop transgenerational transcriptomes unique to the tissue, but common epigenetic control regions in the genome may coordinately regulate these tissue-specific transcriptomes. This systems biology approach provides insight into the molecular mechanisms involved in the epigenetic transgenerational inheritance of a variety of adult onset disease phenotypes. PMID:23034163

Global Transcriptome Analysis of Staphylococcus aureus Response to Hydrogen Peroxide†

PubMed Central

Chang, Wook; Small, David A.; Toghrol, Freshteh; Bentley, William E.

2006-01-01

Staphylococcus aureus responds with protective strategies against phagocyte-derived reactive oxidants to infect humans. Herein, we report the transcriptome analysis of the cellular response of S. aureus to hydrogen peroxide-induced oxidative stress. The data indicate that the oxidative response includes the induction of genes involved in virulence, DNA repair, and notably, anaerobic metabolism. PMID:16452450

Modular organization of the white spruce (Picea glauca) transcriptome reveals functional organization and evolutionary signatures.

PubMed

Raherison, Elie S M; Giguère, Isabelle; Caron, Sébastien; Lamara, Mebarek; MacKay, John J

2015-07-01

Transcript profiling has shown the molecular bases of several biological processes in plants but few studies have developed an understanding of overall transcriptome variation. We investigated transcriptome structure in white spruce (Picea glauca), aiming to delineate its modular organization and associated functional and evolutionary attributes. Microarray analyses were used to: identify and functionally characterize groups of co-expressed genes; investigate expressional and functional diversity of vascular tissue preferential genes which were conserved among Picea species, and identify expression networks underlying wood formation. We classified 22 857 genes as variable (79%; 22 coexpression groups) or invariant (21%) by profiling across several vegetative tissues. Modular organization and complex transcriptome restructuring among vascular tissue preferential genes was revealed by their assignment to coexpression groups with partially overlapping profiles and partially distinct functions. Integrated analyses of tissue-based and temporally variable profiles identified secondary xylem gene networks, showed their remodelling over a growing season and identified PgNAC-7 (no apical meristerm (NAM), Arabidopsis transcription activation factor (ATAF) and cup-shaped cotyledon (CUC) transcription factor 007 in Picea glauca) as a major hub gene specific to earlywood formation. Reference profiling identified comprehensive, statistically robust coexpressed groups, revealing that modular organization underpins the evolutionary conservation of the transcriptome structure. © 2015 The Authors. New Phytologist © 2015 New Phytologist Trust.

ChlamyNET: a Chlamydomonas gene co-expression network reveals global properties of the transcriptome and the early setup of key co-expression patterns in the green lineage.

PubMed

Romero-Campero, Francisco J; Perez-Hurtado, Ignacio; Lucas-Reina, Eva; Romero, Jose M; Valverde, Federico

2016-03-12

Chlamydomonas reinhardtii is the model organism that serves as a reference for studies in algal genomics and physiology. It is of special interest in the study of the evolution of regulatory pathways from algae to higher plants. Additionally, it has recently gained attention as a potential source for bio-fuel and bio-hydrogen production. The genome of Chlamydomonas is available, facilitating the analysis of its transcriptome by RNA-seq data. This has produced a massive amount of data that remains fragmented making necessary the application of integrative approaches based on molecular systems biology. We constructed a gene co-expression network based on RNA-seq data and developed a web-based tool, ChlamyNET, for the exploration of the Chlamydomonas transcriptome. ChlamyNET exhibits a scale-free and small world topology. Applying clustering techniques, we identified nine gene clusters that capture the structure of the transcriptome under the analyzed conditions. One of the most central clusters was shown to be involved in carbon/nitrogen metabolism and signalling, whereas one of the most peripheral clusters was involved in DNA replication and cell cycle regulation. The transcription factors and regulators in the Chlamydomonas genome have been identified in ChlamyNET. The biological processes potentially regulated by them as well as their putative transcription factor binding sites were determined. The putative light regulated transcription factors and regulators in the Chlamydomonas genome were analyzed in order to provide a case study on the use of ChlamyNET. Finally, we used an independent data set to cross-validate the predictive power of ChlamyNET. The topological properties of ChlamyNET suggest that the Chlamydomonas transcriptome posseses important characteristics related to error tolerance, vulnerability and information propagation. The central part of ChlamyNET constitutes the core of the transcriptome where most authoritative hub genes are located interconnecting key biological processes such as light response with carbon and nitrogen metabolism. Our study reveals that key elements in the regulation of carbon and nitrogen metabolism, light response and cell cycle identified in higher plants were already established in Chlamydomonas. These conserved elements are not only limited to transcription factors, regulators and their targets, but also include the cis-regulatory elements recognized by them.

Metastatic breast carcinomas display genomic and transcriptomic heterogeneity

PubMed Central

Weigelt, Britta; Ng, Charlotte KY; Shen, Ronglai; Popova, Tatiana; Schizas, Michail; Natrajan, Rachael; Mariani, Odette; Stern, Marc-Henri; Norton, Larry; Vincent-Salomon, Anne; Reis-Filho, Jorge S

2015-01-01

Metaplastic breast carcinoma is a rare and aggressive histologic type of breast cancer, preferentially displaying a triple-negative phenotype. We sought to define the transcriptomic heterogeneity of metaplastic breast cancers on the basis of current gene expression microarray-based classifiers, and to determine whether these tumors display gene copy number profiles consistent with those of BRCA1-associated breast cancers. Twenty-eight consecutive triple-negative metaplastic breast carcinomas were reviewed, and the metaplastic component present in each frozen specimen was defined (ie, spindle cell, squamous, chondroid metaplasia). RNA and DNA extracted from frozen sections with tumor cell content >60% were subjected to gene expression (Illumina HumanHT-12 v4) and copy number profiling (Affymetrix SNP 6.0), respectively. Using the best practice PAM50/claudin-low microarray-based classifier, all metaplastic breast carcinomas with spindle cell metaplasia were of claudin-low subtype, whereas those with squamous or chondroid metaplasia were preferentially of basal-like subtype. Triple-negative breast cancer subtyping using a dedicated website (http://cbc.mc.vanderbilt.edu/tnbc/) revealed that all metaplastic breast carcinomas with chondroid metaplasia were of mesenchymal-like subtype, spindle cell carcinomas preferentially of unstable or mesenchymal stem-like subtype, and those with squamous metaplasia were of multiple subtypes. None of the cases was classified as immunomodulatory or luminal androgen receptor subtype. Integrative clustering, combining gene expression and gene copy number data, revealed that metaplastic breast carcinomas with spindle cell and chondroid metaplasia were preferentially classified as of integrative clusters 4 and 9, respectively, whereas those with squamous metaplasia were classified into six different clusters. Eight of the 26 metaplastic breast cancers subjected to SNP6 analysis were classified as BRCA1-like. The diversity of histologic features of metaplastic breast carcinomas is reflected at the transcriptomic level, and an association between molecular subtypes and histology was observed. BRCA1-like genomic profiles were found only in a subset (31%) of metaplastic breast cancers, and were not associated with a specific molecular or histologic subtype. PMID:25412848

Horizontal gene transfer of microbial cellulases into nematode genomes is associated with functional assimilation and gene turnover

PubMed Central

2011-01-01

Background Natural acquisition of novel genes from other organisms by horizontal or lateral gene transfer is well established for microorganisms. There is now growing evidence that horizontal gene transfer also plays important roles in the evolution of eukaryotes. Genome-sequencing and EST projects of plant and animal associated nematodes such as Brugia, Meloidogyne, Bursaphelenchus and Pristionchus indicate horizontal gene transfer as a key adaptation towards parasitism and pathogenicity. However, little is known about the functional activity and evolutionary longevity of genes acquired by horizontal gene transfer and the mechanisms favoring such processes. Results We examine the transfer of cellulase genes to the free-living and beetle-associated nematode Pristionchus pacificus, for which detailed phylogenetic knowledge is available, to address predictions by evolutionary theory for successful gene transfer. We used transcriptomics in seven Pristionchus species and three other related diplogastrid nematodes with a well-defined phylogenetic framework to study the evolution of ancestral cellulase genes acquired by horizontal gene transfer. We performed intra-species, inter-species and inter-genic analysis by comparing the transcriptomes of these ten species and tested for cellulase activity in each species. Species with cellulase genes in their transcriptome always exhibited cellulase activity indicating functional integration into the host's genome and biology. The phylogenetic profile of cellulase genes was congruent with the species phylogeny demonstrating gene longevity. Cellulase genes show notable turnover with elevated birth and death rates. Comparison by sequencing of three selected cellulase genes in 24 natural isolates of Pristionchus pacificus suggests these high evolutionary dynamics to be associated with copy number variations and positive selection. Conclusion We could demonstrate functional integration of acquired cellulase genes into the nematode's biology as predicted by theory. Thus, functional assimilation, remarkable gene turnover and selection might represent key features of horizontal gene transfer events in nematodes. PMID:21232122

Horizontal gene transfer of microbial cellulases into nematode genomes is associated with functional assimilation and gene turnover.

PubMed

Mayer, Werner E; Schuster, Lisa N; Bartelmes, Gabi; Dieterich, Christoph; Sommer, Ralf J

2011-01-13

Natural acquisition of novel genes from other organisms by horizontal or lateral gene transfer is well established for microorganisms. There is now growing evidence that horizontal gene transfer also plays important roles in the evolution of eukaryotes. Genome-sequencing and EST projects of plant and animal associated nematodes such as Brugia, Meloidogyne, Bursaphelenchus and Pristionchus indicate horizontal gene transfer as a key adaptation towards parasitism and pathogenicity. However, little is known about the functional activity and evolutionary longevity of genes acquired by horizontal gene transfer and the mechanisms favoring such processes. We examine the transfer of cellulase genes to the free-living and beetle-associated nematode Pristionchus pacificus, for which detailed phylogenetic knowledge is available, to address predictions by evolutionary theory for successful gene transfer. We used transcriptomics in seven Pristionchus species and three other related diplogastrid nematodes with a well-defined phylogenetic framework to study the evolution of ancestral cellulase genes acquired by horizontal gene transfer. We performed intra-species, inter-species and inter-genic analysis by comparing the transcriptomes of these ten species and tested for cellulase activity in each species. Species with cellulase genes in their transcriptome always exhibited cellulase activity indicating functional integration into the host's genome and biology. The phylogenetic profile of cellulase genes was congruent with the species phylogeny demonstrating gene longevity. Cellulase genes show notable turnover with elevated birth and death rates. Comparison by sequencing of three selected cellulase genes in 24 natural isolates of Pristionchus pacificus suggests these high evolutionary dynamics to be associated with copy number variations and positive selection. We could demonstrate functional integration of acquired cellulase genes into the nematode's biology as predicted by theory. Thus, functional assimilation, remarkable gene turnover and selection might represent key features of horizontal gene transfer events in nematodes.

Elucidating the transcriptome of Fasciola hepatica - a key to fundamental and biotechnological discoveries for a neglected parasite.

PubMed

Young, Neil D; Hall, Ross S; Jex, Aaron R; Cantacessi, Cinzia; Gasser, Robin B

2010-01-01

Liver flukes of animals are parasitic flatworms (Platyhelminthes: Digenea) of major socioeconomic importance in many countries. Key representatives, such as Fasciola hepatica and F. gigantica, cause "liver fluke disease" (= fascioliasis), which is of major animal health significance worldwide. In particular, F. hepatica is a leading cause of production losses to the livestock (mainly sheep and cattle) and meat industries due to clinical disease, reduced weight gain and milk production, and deaths. This parasite is also a major food-borne pathogen of humans throughout parts of the Middle East, Asia and South America. Currently, there is a significant focus on the development of new approaches for the prevention and control of fascioliasis in livestock. Recent technological advances in genomics and bioinformatics provide unique opportunities for the identification and prevalidation of drug targets and vaccines through a better understanding of the biology of F. hepatica and related species as well as their relationship with their hosts at the molecular level. Surprisingly, despite the widespread socioeconomic impact of fascioliasis, genomic datasets for F. hepatica are scant, limiting the molecular biological research of this parasite. The present article explores specifically the transcriptome of the adult stage of F. hepatica using an integrated genomic-bioinformatic platform. The analysis of the current data reveals numerous molecules of biological relevance, some of which are inferred to be involved in key biological processes or pathways that could serve as targets for new trematocidal drugs or vaccines. Improved insights into the transcriptome of F. hepatica should pave the way for future, comparative analysis of the transcriptomes of other developmental stages of this and related parasites, such as F. gigantica, cancer-causing flatworms (Clonorchis sinensis and Opisthorchis viverrini) and blood flukes (Schistosoma mansoni and S. japonicum). Prediction of the essentiality of genes and their products, molecular network connectivity of trematode genes as well as experimental exploration of function should also add value to the genomic discovery efforts in the future, focused on biotechnological outcomes. Copyright 2009 Elsevier Inc. All rights reserved.

iSeq: Web-Based RNA-seq Data Analysis and Visualization.

PubMed

Zhang, Chao; Fan, Caoqi; Gan, Jingbo; Zhu, Ping; Kong, Lei; Li, Cheng

2018-01-01

Transcriptome sequencing (RNA-seq) is becoming a standard experimental methodology for genome-wide characterization and quantification of transcripts at single base-pair resolution. However, downstream analysis of massive amount of sequencing data can be prohibitively technical for wet-lab researchers. A functionally integrated and user-friendly platform is required to meet this demand. Here, we present iSeq, an R-based Web server, for RNA-seq data analysis and visualization. iSeq is a streamlined Web-based R application under the Shiny framework, featuring a simple user interface and multiple data analysis modules. Users without programming and statistical skills can analyze their RNA-seq data and construct publication-level graphs through a standardized yet customizable analytical pipeline. iSeq is accessible via Web browsers on any operating system at http://iseq.cbi.pku.edu.cn .

TranslatomeDB: a comprehensive database and cloud-based analysis platform for translatome sequencing data.

PubMed

Liu, Wanting; Xiang, Lunping; Zheng, Tingkai; Jin, Jingjie; Zhang, Gong

2018-01-04

Translation is a key regulatory step, linking transcriptome and proteome. Two major methods of translatome investigations are RNC-seq (sequencing of translating mRNA) and Ribo-seq (ribosome profiling). To facilitate the investigation of translation, we built a comprehensive database TranslatomeDB (http://www.translatomedb.net/) which provides collection and integrated analysis of published and user-generated translatome sequencing data. The current version includes 2453 Ribo-seq, 10 RNC-seq and their 1394 corresponding mRNA-seq datasets in 13 species. The database emphasizes the analysis functions in addition to the dataset collections. Differential gene expression (DGE) analysis can be performed between any two datasets of same species and type, both on transcriptome and translatome levels. The translation indices translation ratios, elongation velocity index and translational efficiency can be calculated to quantitatively evaluate translational initiation efficiency and elongation velocity, respectively. All datasets were analyzed using a unified, robust, accurate and experimentally-verifiable pipeline based on the FANSe3 mapping algorithm and edgeR for DGE analyzes. TranslatomeDB also allows users to upload their own datasets and utilize the identical unified pipeline to analyze their data. We believe that our TranslatomeDB is a comprehensive platform and knowledgebase on translatome and proteome research, releasing the biologists from complex searching, analyzing and comparing huge sequencing data without needing local computational power. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Not All Biofluids Are Created Equal: Chewing Over Salivary Diagnostics and the Epigenome

PubMed Central

Wren, M.E.; Shirtcliff, E.A.; Drury, Stacy S.

2015-01-01

Purpose This article describes progress to date in the characterization of the salivary epigenome and considers the importance of previous work in the salivary microbiome, proteome, endocrine analytes, genome, and transcriptome. Methods PubMed and Web of Science were used to extensively search the existing literature (original research and reviews) related to salivary diagnostics and bio-marker development, of which 125 studies were examined. This article was derived from the most relevant 73 sources highlighting the recent state of the evolving field of salivary epigenomics and contributing significantly to the foundational work in saliva-based research. Findings Validation of any new saliva-based diagnostic or analyte will require comparison to previously accepted standards established in blood. Careful attention to the collection, processing, and analysis of salivary analytes is critical for the development and implementation of newer applications that include genomic, transcriptomic, and epigenomic markers. All these factors must be integrated into initial study design. Implications This commentary highlights the appeal of the salivary epigenome for translational applications and its utility in future studies of development and the interface among environment, disease, and health. PMID:25778408

Transcriptomic Analysis of Phenotypic Changes in Birch (Betula platyphylla) Autotetraploids

PubMed Central

Mu, Huai-Zhi; Liu, Zi-Jia; Lin, Lin; Li, Hui-Yu; Jiang, Jing; Liu, Gui-Feng

2012-01-01

Plant breeders have focused much attention on polyploid trees because of their importance to forestry. To evaluate the impact of intraspecies genome duplication on the transcriptome, a series of Betula platyphylla autotetraploids and diploids were generated from four full-sib families. The phenotypes and transcriptomes of these autotetraploid individuals were compared with those of diploid trees. Autotetraploids were generally superior in breast-height diameter, volume, leaf, fruit and stoma and were generally inferior in height compared to diploids. Transcriptome data revealed numerous changes in gene expression attributable to autotetraploidization, which resulted in the upregulation of 7052 unigenes and the downregulation of 3658 unigenes. Pathway analysis revealed that the biosynthesis and signal transduction of indoleacetate (IAA) and ethylene were altered after genome duplication, which may have contributed to phenotypic changes. These results shed light on variations in birch autotetraploidization and help identify important genes for the genetic engineering of birch trees. PMID:23202935

Transcriptomic analysis of the hepatic response to stress in the red cusk-eel (Genypterus chilensis): Insights into lipid metabolism, oxidative stress and liver steatosis

PubMed Central

Aedo, Jorge E.; Zuloaga, Rodrigo; Maldonado, Jonathan; Bastias-Molina, Macarena; Silva, Herman; Meneses, Claudio; Gallardo-Escarate, Cristian; Molina, Alfredo

2017-01-01

Teleosts exhibit a broad divergence in their adaptive response to stress, depending on the magnitude, duration, and frequency of stressors and the species receiving the stimulus. We have previously reported that the red cusk-eel (Genypterus chilensis), an important marine farmed fish, shows a physiological response to stress that results in increased skeletal muscle atrophy mediated by over-expression of components of the ubiquitin proteasome and autophagy-lysosomal systems. To better understand the systemic effects of stress on the red cusk-eel metabolism, the present study assessed the transcriptomic hepatic response to repetitive handling-stress. Using high-throughput RNA-seq, 259 up-regulated transcripts were found, mostly associated with angiogenesis, gluconeogenesis, and triacylglyceride catabolism. Conversely, 293 transcripts were down-regulated, associated to cholesterol biosynthesis, PPARα signaling, fatty acid biosynthesis, and glycolysis. This gene signature was concordant with hepatic metabolite levels and hepatic oxidative damage. Moreover, the increased plasmatic levels of AST (aspartate aminotransferase), ALT (alanine aminotransferase) and AP (alkaline phosphatase), as well as liver histology suggest stress-induced liver steatosis. This study offers an integrative molecular and biochemical analysis of the hepatic response to handling-stress, and reveals unknown aspects of lipid metabolism in a non-model teleost. PMID:28448552

Genetic analysis of interferon induced thyroiditis (IIT): evidence for a key role for MHC and apoptosis related genes and pathways.

PubMed

Hasham, Alia; Zhang, Weijia; Lotay, Vaneet; Haggerty, Shannon; Stefan, Mihaela; Concepcion, Erlinda; Dieterich, Douglas T; Tomer, Yaron

2013-08-01

Autoimmune thyroid diseases (AITD) have become increasingly recognized as a complication of interferon-alpha (IFNα) therapy in patients with chronic Hepatitis C virus (HCV) infection. Interferon-induced thyroiditis (IIT) can manifest as clinical thyroiditis in approximately 15% of HCV patients receiving IFNα and subclinical thyroiditis in up to 40% of patients, possibly resulting in either dose reduction or discontinuation of IFNα treatment. However, the exact mechanisms that lead to the development of IIT are unknown and may include IFNα-mediated immune-recruitment as well as direct toxic effects on thyroid follicular cells. We hypothesized that IIT develops in genetically predisposed individuals whose threshold for developing thyroiditis is lowered by IFNα. Therefore, our aim was to identify the susceptibility genes for IIT. We used a genomic convergence approach combining genetic association data with transcriptome analysis of genes upregulated by IFNα. Integrating results of genetic association, transcriptome data, pathway, and haplotype analyses enabled the identification of 3 putative loci, SP100/110/140 (2q37.1), HLA (6p21.3), and TAP1 (6p21.3) that may be involved in the pathogenesis of IIT. Immune-regulation and apoptosis emerged as the predominant mechanisms underlying the etiology of IIT. Published by Elsevier Ltd.

GENETIC ANALYSIS OF INTERFERON INDUCED THYROIDITIS (IIT): EVIDENCE FOR A KEY ROLE FOR MHC AND APOPTOSIS RELATED GENES AND PATHWAYS

PubMed Central

Hasham, Alia; Zhang, Weijia; Lotay, Vaneet; Haggerty, Shannon; Stefan, Mihaela; Concepcion, Erlinda; Dieterich, Douglas T.; Tomer, Yaron

2013-01-01

Autoimmune thyroid diseases (AITD) have become increasingly recognized as a complication of interferon-alpha (IFNα) therapy in patients with chronic Hepatitis C virus (HCV) infection. Interferon-induced thyroiditis (IIT) can manifest as clinical thyroiditis in approximately 15% of HCV patients receiving IFNα and subclinical thyroiditis in up to 40% of patients, possibly resulting in either dose reduction or discontinuation of IFNα treatment. However, the exact mechanisms that lead to the development of IIT are unknown and may include IFNα-mediated immune-recruitment as well as direct toxic effects on thyroid follicular cells. We hypothesized that IIT develops in genetically predisposed individuals whose threshold for developing thyroiditis is lowered by IFNα. Therefore, our aim was to identify the susceptibility genes for IIT. We used a genomic convergence approach combining genetic association data with transcriptome analysis of genes upregulated by IFNα. Integrating results of genetic association, transcriptome data, pathway, and haplotype analyses enabled the identification of 3 putative loci, SP100/110/140 (2q37.1), HLA (6p21.3), and TAP1 (6p21.3) that may be involved in the pathogenesis of IIT. Immune-regulation and apoptosis emerged as the predominant mechanisms underlying the etiology of IIT. PMID:23683877

Transcriptome analysis by strand-specific sequencing of complementary DNA

PubMed Central

Parkhomchuk, Dmitri; Borodina, Tatiana; Amstislavskiy, Vyacheslav; Banaru, Maria; Hallen, Linda; Krobitsch, Sylvia; Lehrach, Hans; Soldatov, Alexey

2009-01-01

High-throughput complementary DNA sequencing (RNA-Seq) is a powerful tool for whole-transcriptome analysis, supplying information about a transcript's expression level and structure. However, it is difficult to determine the polarity of transcripts, and therefore identify which strand is transcribed. Here, we present a simple cDNA sequencing protocol that preserves information about a transcript's direction. Using Saccharomyces cerevisiae and mouse brain transcriptomes as models, we demonstrate that knowing the transcript's orientation allows more accurate determination of the structure and expression of genes. It also helps to identify new genes and enables studying promoter-associated and antisense transcription. The transcriptional landscapes we obtained are available online. PMID:19620212

Transcriptome analysis by strand-specific sequencing of complementary DNA.

PubMed

Parkhomchuk, Dmitri; Borodina, Tatiana; Amstislavskiy, Vyacheslav; Banaru, Maria; Hallen, Linda; Krobitsch, Sylvia; Lehrach, Hans; Soldatov, Alexey

2009-10-01

High-throughput complementary DNA sequencing (RNA-Seq) is a powerful tool for whole-transcriptome analysis, supplying information about a transcript's expression level and structure. However, it is difficult to determine the polarity of transcripts, and therefore identify which strand is transcribed. Here, we present a simple cDNA sequencing protocol that preserves information about a transcript's direction. Using Saccharomyces cerevisiae and mouse brain transcriptomes as models, we demonstrate that knowing the transcript's orientation allows more accurate determination of the structure and expression of genes. It also helps to identify new genes and enables studying promoter-associated and antisense transcription. The transcriptional landscapes we obtained are available online.

Multi-omic integrated networks connect DNA methylation and miRNA with skeletal muscle plasticity to chronic exercise in Type 2 diabetic obesity.

PubMed

Rowlands, David S; Page, Rachel A; Sukala, William R; Giri, Mamta; Ghimbovschi, Svetlana D; Hayat, Irum; Cheema, Birinder S; Lys, Isabelle; Leikis, Murray; Sheard, Phillip W; Wakefield, St John; Breier, Bernhard; Hathout, Yetrib; Brown, Kristy; Marathi, Ramya; Orkunoglu-Suer, Funda E; Devaney, Joseph M; Leiken, Benjamin; Many, Gina; Krebs, Jeremy; Hopkins, Will G; Hoffman, Eric P

2014-10-15

Epigenomic regulation of the transcriptome by DNA methylation and posttranscriptional gene silencing by miRNAs are potential environmental modulators of skeletal muscle plasticity to chronic exercise in healthy and diseased populations. We utilized transcriptome networks to connect exercise-induced differential methylation and miRNA with functional skeletal muscle plasticity. Biopsies of the vastus lateralis were collected from middle-aged Polynesian men and women with morbid obesity (44 kg/m(2) ± 10) and Type 2 diabetes before and following 16 wk of resistance (n = 9) or endurance training (n = 8). Longitudinal transcriptome, methylome, and microRNA (miRNA) responses were obtained via microarray, filtered by novel effect-size based false discovery rate probe selection preceding bioinformatic interrogation. Metabolic and microvascular transcriptome topology dominated the network landscape following endurance exercise. Lipid and glucose metabolism modules were connected to: microRNA (miR)-29a; promoter region hypomethylation of nuclear receptor factor (NRF1) and fatty acid transporter (SLC27A4), and hypermethylation of fatty acid synthase, and to exon hypomethylation of 6-phosphofructo-2-kinase and Ser/Thr protein kinase. Directional change in the endurance networks was validated by lower intramyocellular lipid, increased capillarity, GLUT4, hexokinase, and mitochondrial enzyme activity and proteome. Resistance training also lowered lipid and increased enzyme activity and caused GLUT4 promoter hypomethylation; however, training was inconsequential to GLUT4, capillarity, and metabolic transcriptome. miR-195 connected to negative regulation of vascular development. To conclude, integrated molecular network modelling revealed differential DNA methylation and miRNA expression changes occur in skeletal muscle in response to chronic exercise training that are most pronounced with endurance training and topographically associated with functional metabolic and microvascular plasticity relevant to diabetes rehabilitation. Copyright © 2014 the American Physiological Society.

An integrated omic analysis of hepatic alteration in medaka fish chronically exposed to cyanotoxins with possible mechanisms of reproductive toxicity.

PubMed

Qiao, Qin; Le Manach, Séverine; Huet, Hélène; Duvernois-Berthet, Evelyne; Chaouch, Soraya; Duval, Charlotte; Sotton, Benoit; Ponger, Loïc; Marie, Arul; Mathéron, Lucrèce; Lennon, Sarah; Bolbach, Gérard; Djediat, Chakib; Bernard, Cécile; Edery, Marc; Marie, Benjamin

2016-12-01

Cyanobacterial blooms threaten human health as well as the population of other living organisms in the aquatic environment, particularly due to the production of natural toxic components, the cyanotoxin. So far, the most studied cyanotoxins are microcystins (MCs). In this study, the hepatic alterations at histological, proteome and transcriptome levels were evaluated in female and male medaka fish chronically exposed to 1 and 5 μg L -1 microcystin-LR (MC-LR) and to the extract of MC-producing Microcystis aeruginosa PCC 7820 (5 μg L -1 of equivalent MC-LR) by balneation for 28 days, aiming at enhancing our understanding of the potential reproductive toxicity of cyanotoxins in aquatic vertebrate models. Indeed, both MC and Microcystis extract adversely affect reproductive parameters including fecundity and egg hatchability. The liver of toxin treated female fish present glycogen storage loss and cellular damages. The quantitative proteomics analysis revealed that the quantities of 225 hepatic proteins are dysregulated. In particular, a notable decrease in protein quantities of vitellogenin and choriogenin was observed, which could explain the decrease in reproductive output. Liver transcriptome analysis through Illumina RNA-seq reveals that over 100-400 genes are differentially expressed under 5 μg L -1  MC-LR and Microcystis extract treatments, respectively. Ingenuity pathway analysis of the omic data attests that various metabolic pathways, such as energy production, protein biosynthesis and lipid metabolism, are disturbed by both MC-LR and the Microcystis extract, which could provoke the observed reproductive impairment. The transcriptomics analysis also constitutes the first report of the impairment of circadian rhythm-related gene induced by MCs. This study contributes to a better understanding of the potential consequences of chronic exposure of fish to environmental concentrations of cyanotoxins, suggesting that Microcystis extract could impact a wider range of biological pathways, compared with pure MC-LR, and even 1 μg L -1  MC-LR potentially induces a health risk for aquatic organisms. Copyright © 2016 Elsevier Ltd. All rights reserved.

Integrative eQTL analysis of tumor and host omics data in individuals with bladder cancer.

PubMed

Pineda, Silvia; Van Steen, Kristel; Malats, Núria

2017-09-01

Integrative analyses of several omics data are emerging. The data are usually generated from the same source material (i.e., tumor sample) representing one level of regulation. However, integrating different regulatory levels (i.e., blood) with those from tumor may also reveal important knowledge about the human genetic architecture. To model this multilevel structure, an integrative-expression quantitative trait loci (eQTL) analysis applying two-stage regression (2SR) was proposed. This approach first regressed tumor gene expression levels with tumor markers and the adjusted residuals from the previous model were then regressed with the germline genotypes measured in blood. Previously, we demonstrated that penalized regression methods in combination with a permutation-based MaxT method (Global-LASSO) is a promising tool to fix some of the challenges that high-throughput omics data analysis imposes. Here, we assessed whether Global-LASSO can also be applied when tumor and blood omics data are integrated. We further compared our strategy with two 2SR-approaches, one using multiple linear regression (2SR-MLR) and other using LASSO (2SR-LASSO). We applied the three models to integrate genomic, epigenomic, and transcriptomic data from tumor tissue with blood germline genotypes from 181 individuals with bladder cancer included in the TCGA Consortium. Global-LASSO provided a larger list of eQTLs than the 2SR methods, identified a previously reported eQTLs in prostate stem cell antigen (PSCA), and provided further clues on the complexity of APBEC3B loci, with a minimal false-positive rate not achieved by 2SR-MLR. It also represents an important contribution for omics integrative analysis because it is easy to apply and adaptable to any type of data. © 2017 WILEY PERIODICALS, INC.

Comparative transcriptome analysis of the CO2 sensing pathway via differential expression of carbonic anhydrase in Cryptococcus neoformans.

PubMed

Kim, Min Su; Ko, Young-Joon; Maeng, Shinae; Floyd, Anna; Heitman, Joseph; Bahn, Yong-Sun

2010-08-01

Carbon dioxide (CO(2)) sensing and metabolism via carbonic anhydrases (CAs) play pivotal roles in survival and proliferation of pathogenic fungi infecting human hosts from natural environments due to the drastic difference in CO(2) levels. In Cryptococcus neoformans, which causes fatal fungal meningoencephalitis, the Can2 CA plays essential roles during both cellular growth in air and sexual differentiation of the pathogen. However the signaling networks downstream of Can2 are largely unknown. To address this question, the present study employed comparative transcriptome DNA microarray analysis of a C. neoformans strain in which CAN2 expression is artificially controlled by the CTR4 (copper transporter) promoter. The P(CTR4)CAN2 strain showed growth defects in a CO(2)-dependent manner when CAN2 was repressed but resumed normal growth when CAN2 was overexpressed. The Can2-dependent genes identified by the transcriptome analysis include FAS1 (fatty acid synthase 1) and GPB1 (G-protein beta subunit), supporting the roles of Can2 in fatty acid biosynthesis and sexual differentiation. Cas3, a capsular structure designer protein, was also discovered to be Can2-dependent and yet was not involved in CO(2)-mediated capsule induction. Most notably, a majority of Can2-dependent genes were environmental stress-regulated (ESR) genes. Supporting this, the CAN2 overexpression strain was hypersensitive to oxidative and genotoxic stress as well as antifungal drugs, such as polyene and azole drugs, potentially due to defective membrane integrity. Finally, an oxidative stress-responsive Atf1 transcription factor was also found to be Can2-dependent. Atf1 not only plays an important role in diverse stress responses, including thermotolerance and antifungal drug resistance, but also represses melanin and capsule production in C. neoformans. In conclusion, this study provides insights into the comprehensive signaling networks orchestrated by CA/CO(2)-sensing pathways in pathogenic fungi.

Transcriptome- Assisted Label-Free Quantitative Proteomics Analysis Reveals Novel Insights into Piper nigrum—Phytophthora capsici Phytopathosystem

PubMed Central

Mahadevan, Chidambareswaren; Krishnan, Anu; Saraswathy, Gayathri G.; Surendran, Arun; Jaleel, Abdul; Sakuntala, Manjula

2016-01-01

Black pepper (Piper nigrum L.), a tropical spice crop of global acclaim, is susceptible to Phytophthora capsici, an oomycete pathogen which causes the highly destructive foot rot disease. A systematic understanding of this phytopathosystem has not been possible owing to lack of genome or proteome information. In this study, we explain an integrated transcriptome-assisted label-free quantitative proteomics pipeline to study the basal immune components of black pepper when challenged with P. capsici. We report a global identification of 532 novel leaf proteins from black pepper, of which 518 proteins were functionally annotated using BLAST2GO tool. A label-free quantitation of the protein datasets revealed 194 proteins common to diseased and control protein datasets of which 22 proteins showed significant up-regulation and 134 showed significant down-regulation. Ninety-three proteins were identified exclusively on P. capsici infected leaf tissues and 245 were expressed only in mock (control) infected samples. In-depth analysis of our data gives novel insights into the regulatory pathways of black pepper which are compromised during the infection. Differential down-regulation was observed in a number of critical pathways like carbon fixation in photosynthetic organism, cyano-amino acid metabolism, fructose, and mannose metabolism, glutathione metabolism, and phenylpropanoid biosynthesis. The proteomics results were validated with real-time qRT-PCR analysis. We were also able to identify the complete coding sequences for all the proteins of which few selected genes were cloned and sequence characterized for further confirmation. Our study is the first report of a quantitative proteomics dataset in black pepper which provides convincing evidence on the effectiveness of a transcriptome-based label-free proteomics approach for elucidating the host response to biotic stress in a non-model spice crop like P. nigrum, for which genome information is unavailable. Our dataset will serve as a useful resource for future studies in this plant. Data are available via ProteomeXchange with identifier PXD003887. PMID:27379110

Transcriptome- Assisted Label-Free Quantitative Proteomics Analysis Reveals Novel Insights into Piper nigrum-Phytophthora capsici Phytopathosystem.

PubMed

Mahadevan, Chidambareswaren; Krishnan, Anu; Saraswathy, Gayathri G; Surendran, Arun; Jaleel, Abdul; Sakuntala, Manjula

2016-01-01

Black pepper (Piper nigrum L.), a tropical spice crop of global acclaim, is susceptible to Phytophthora capsici, an oomycete pathogen which causes the highly destructive foot rot disease. A systematic understanding of this phytopathosystem has not been possible owing to lack of genome or proteome information. In this study, we explain an integrated transcriptome-assisted label-free quantitative proteomics pipeline to study the basal immune components of black pepper when challenged with P. capsici. We report a global identification of 532 novel leaf proteins from black pepper, of which 518 proteins were functionally annotated using BLAST2GO tool. A label-free quantitation of the protein datasets revealed 194 proteins common to diseased and control protein datasets of which 22 proteins showed significant up-regulation and 134 showed significant down-regulation. Ninety-three proteins were identified exclusively on P. capsici infected leaf tissues and 245 were expressed only in mock (control) infected samples. In-depth analysis of our data gives novel insights into the regulatory pathways of black pepper which are compromised during the infection. Differential down-regulation was observed in a number of critical pathways like carbon fixation in photosynthetic organism, cyano-amino acid metabolism, fructose, and mannose metabolism, glutathione metabolism, and phenylpropanoid biosynthesis. The proteomics results were validated with real-time qRT-PCR analysis. We were also able to identify the complete coding sequences for all the proteins of which few selected genes were cloned and sequence characterized for further confirmation. Our study is the first report of a quantitative proteomics dataset in black pepper which provides convincing evidence on the effectiveness of a transcriptome-based label-free proteomics approach for elucidating the host response to biotic stress in a non-model spice crop like P. nigrum, for which genome information is unavailable. Our dataset will serve as a useful resource for future studies in this plant. Data are available via ProteomeXchange with identifier PXD003887.

Integrated transcriptomic and proteomic analysis of the bile stress response in probiotic Lactobacillus salivarius LI01.

PubMed

Lv, Long-Xian; Yan, Ren; Shi, Hai-Yan; Shi, Ding; Fang, Dai-Qiong; Jiang, Hui-Yong; Wu, Wen-Rui; Guo, Fei-Fei; Jiang, Xia-Wei; Gu, Si-Lan; Chen, Yun-Bo; Yao, Jian; Li, Lan-Juan

2017-01-06

Lactobacillus salivarius LI01, isolated from healthy humans, has demonstrated probiotic properties in the prevention and treatment of liver failure. Tolerance to bile stress is crucial to allow lactobacilli to survive in the gastrointestinal tract and exert their benefits. In this work, we used a Digital Gene Expression transcriptomic and iTRAQ LC-MS/MS proteomic approach to examine the characteristics of LI01 in response to bile stress. Using culture medium with or without 0.15% ox bile, 591 differentially transcribed genes and 347 differentially expressed proteins were detected in LI01. Overall, we found the bile resistance of LI01 to be based on a highly remodeled cell envelope and a reinforced bile efflux system rather than on the activity of bile salt hydrolases. Additionally, some differentially expressed genes related to regulatory systems, the general stress response and central metabolism processes, also play roles in stress sensing, bile-induced damage prevention and energy efficiency. Moreover, bile salts appear to enhance proteolysis and amino acid uptake (especially aromatic amino acids) by LI01, which may support the liver protection properties of this strain. Altogether, this study establishes a model of global response mechanism to bile stress in L. salivarius LI01. L. salivarius strain LI01 exhibits not only antibacterial and antifungal properties but also exerts a good health-promoting effect in acute liver failure. As a potential probiotic strain, the bile-tolerance trait of strain LI01 is important, though this has not yet been explored. In this study, an analysis based on DGE and iTRAQ was performed to investigate the gene expression in strain LI01 under bile stress at the mRNA and protein levels, respectively. To our knowledge, this work also represents the first combined transcriptomic and proteomic analysis of the bile stress response mechanism in L. salivarius. Copyright © 2016. Published by Elsevier B.V.

Coral-zooxanthellae meta-transcriptomics reveals integrated response to pollutant stress.

PubMed

Gust, Kurt A; Najar, Fares Z; Habib, Tanwir; Lotufo, Guilherme R; Piggot, Alan M; Fouke, Bruce W; Laird, Jennifer G; Wilbanks, Mitchell S; Rawat, Arun; Indest, Karl J; Roe, Bruce A; Perkins, Edward J

2014-07-12

Corals represent symbiotic meta-organisms that require harmonization among the coral animal, photosynthetic zooxanthellae and associated microbes to survive environmental stresses. We investigated integrated-responses among coral and zooxanthellae in the scleractinian coral Acropora formosa in response to an emerging marine pollutant, the munitions constituent, 1,3,5-trinitro-1,3,5 triazine (RDX; 5 day exposures to 0 (control), 0.5, 0.9, 1.8, 3.7, and 7.2 mg/L, measured in seawater). RDX accumulated readily in coral soft tissues with bioconcentration factors ranging from 1.1 to 1.5. Next-generation sequencing of a normalized meta-transcriptomic library developed for the eukaryotic components of the A. formosa coral holobiont was leveraged to conduct microarray-based global transcript expression analysis of integrated coral/zooxanthellae responses to the RDX exposure. Total differentially expressed transcripts (DET) increased with increasing RDX exposure concentrations as did the proportion of zooxanthellae DET relative to the coral animal. Transcriptional responses in the coral demonstrated higher sensitivity to RDX compared to zooxanthellae where increased expression of gene transcripts coding xenobiotic detoxification mechanisms (i.e. cytochrome P450 and UDP glucuronosyltransferase 2 family) were initiated at the lowest exposure concentration. Increased expression of these detoxification mechanisms was sustained at higher RDX concentrations as well as production of a physical barrier to exposure through a 40% increase in mucocyte density at the maximum RDX exposure. At and above the 1.8 mg/L exposure concentration, DET coding for genes involved in central energy metabolism, including photosynthesis, glycolysis and electron-transport functions, were decreased in zooxanthellae although preliminary data indicated that zooxanthellae densities were not affected. In contrast, significantly increased transcript expression for genes involved in cellular energy production including glycolysis and electron-transport pathways was observed in the coral animal. Transcriptional network analysis for central energy metabolism demonstrated highly correlated responses to RDX among the coral animal and zooxanthellae indicative of potential compensatory responses to lost photosynthetic potential within the holobiont. These observations underscore the potential for complex integrated responses to RDX exposure among species comprising the coral holobiont and highlight the need to understand holobiont-species interactions to accurately assess pollutant impacts.

Pyrosequencing the Bemisia tabaci Transcriptome Reveals a Highly Diverse Bacterial Community and a Robust System for Insecticide Resistance

PubMed Central

Wu, Qing-jun; Wang, Shao-li; Yang, Xin; Yang, Ni-na; Li, Ru-mei; Jiao, Xiao-guo; Pan, Hui-peng; Liu, Bai-ming; Su, Qi; Xu, Bao-yun; Hu, Song-nian; Zhou, Xu-guo; Zhang, You-jun

2012-01-01

Background Bemisia tabaci (Gennadius) is a phloem-feeding insect poised to become one of the major insect pests in open field and greenhouse production systems throughout the world. The high level of resistance to insecticides is a main factor that hinders continued use of insecticides for suppression of B. tabaci. Despite its prevalence, little is known about B. tabaci at the genome level. To fill this gap, an invasive B. tabaci B biotype was subjected to pyrosequencing-based transcriptome analysis to identify genes and gene networks putatively involved in various physiological and toxicological processes. Methodology and Principal Findings Using Roche 454 pyrosequencing, 857,205 reads containing approximately 340 megabases were obtained from the B. tabaci transcriptome. De novo assembly generated 178,669 unigenes including 30,980 from insects, 17,881 from bacteria, and 129,808 from the nohit. A total of 50,835 (28.45%) unigenes showed similarity to the non-redundant database in GenBank with a cut-off E-value of 10–5. Among them, 40,611 unigenes were assigned to one or more GO terms and 6,917 unigenes were assigned to 288 known pathways. De novo metatranscriptome analysis revealed highly diverse bacterial symbionts in B. tabaci, and demonstrated the host-symbiont cooperation in amino acid production. In-depth transcriptome analysis indentified putative molecular markers, and genes potentially involved in insecticide resistance and nutrient digestion. The utility of this transcriptome was validated by a thiamethoxam resistance study, in which annotated cytochrome P450 genes were significantly overexpressed in the resistant B. tabaci in comparison to its susceptible counterparts. Conclusions This transcriptome/metatranscriptome analysis sheds light on the molecular understanding of symbiosis and insecticide resistance in an agriculturally important phloem-feeding insect pest, and lays the foundation for future functional genomics research of the B. tabaci complex. Moreover, current pyrosequencing effort greatly enriched the existing whitefly EST database, and makes RNAseq a viable option for future genomic analysis. PMID:22558125

Comprehensive evaluation of AmpliSeq transcriptome, a novel targeted whole transcriptome RNA sequencing methodology for global gene expression analysis.

PubMed

Li, Wenli; Turner, Amy; Aggarwal, Praful; Matter, Andrea; Storvick, Erin; Arnett, Donna K; Broeckel, Ulrich

2015-12-16

Whole transcriptome sequencing (RNA-seq) represents a powerful approach for whole transcriptome gene expression analysis. However, RNA-seq carries a few limitations, e.g., the requirement of a significant amount of input RNA and complications led by non-specific mapping of short reads. The Ion AmpliSeq Transcriptome Human Gene Expression Kit (AmpliSeq) was recently introduced by Life Technologies as a whole-transcriptome, targeted gene quantification kit to overcome these limitations of RNA-seq. To assess the performance of this new methodology, we performed a comprehensive comparison of AmpliSeq with RNA-seq using two well-established next-generation sequencing platforms (Illumina HiSeq and Ion Torrent Proton). We analyzed standard reference RNA samples and RNA samples obtained from human induced pluripotent stem cell derived cardiomyocytes (hiPSC-CMs). Using published data from two standard RNA reference samples, we observed a strong concordance of log2 fold change for all genes when comparing AmpliSeq to Illumina HiSeq (Pearson's r = 0.92) and Ion Torrent Proton (Pearson's r = 0.92). We used ROC, Matthew's correlation coefficient and RMSD to determine the overall performance characteristics. All three statistical methods demonstrate AmpliSeq as a highly accurate method for differential gene expression analysis. Additionally, for genes with high abundance, AmpliSeq outperforms the two RNA-seq methods. When analyzing four closely related hiPSC-CM lines, we show that both AmpliSeq and RNA-seq capture similar global gene expression patterns consistent with known sources of variations. Our study indicates that AmpliSeq excels in the limiting areas of RNA-seq for gene expression quantification analysis. Thus, AmpliSeq stands as a very sensitive and cost-effective approach for very large scale gene expression analysis and mRNA marker screening with high accuracy.

Transcriptome-Based Characterization of Interactions between Saccharomyces cerevisiae and Lactobacillus delbrueckii subsp. bulgaricus in Lactose-Grown Chemostat Cocultures

PubMed Central

Mendes, Filipa; Sieuwerts, Sander; de Hulster, Erik; Almering, Marinka J. H.; Luttik, Marijke A. H.; Pronk, Jack T.; Smid, Eddy J.; Bron, Peter A.

2013-01-01

Mixed populations of Saccharomyces cerevisiae yeasts and lactic acid bacteria occur in many dairy, food, and beverage fermentations, but knowledge about their interactions is incomplete. In the present study, interactions between Saccharomyces cerevisiae and Lactobacillus delbrueckii subsp. bulgaricus, two microorganisms that co-occur in kefir fermentations, were studied during anaerobic growth on lactose. By combining physiological and transcriptome analysis of the two strains in the cocultures, five mechanisms of interaction were identified. (i) Lb. delbrueckii subsp. bulgaricus hydrolyzes lactose, which cannot be metabolized by S. cerevisiae, to galactose and glucose. Subsequently, galactose, which cannot be metabolized by Lb. delbrueckii subsp. bulgaricus, is excreted and provides a carbon source for yeast. (ii) In pure cultures, Lb. delbrueckii subsp. bulgaricus grows only in the presence of increased CO2 concentrations. In anaerobic mixed cultures, the yeast provides this CO2 via alcoholic fermentation. (iii) Analysis of amino acid consumption from the defined medium indicated that S. cerevisiae supplied alanine to the bacterium. (iv) A mild but significant low-iron response in the yeast transcriptome, identified by DNA microarray analysis, was consistent with the chelation of iron by the lactate produced by Lb. delbrueckii subsp. bulgaricus. (v) Transcriptome analysis of Lb. delbrueckii subsp. bulgaricus in mixed cultures showed an overrepresentation of transcripts involved in lipid metabolism, suggesting either a competition of the two microorganisms for fatty acids or a response to the ethanol produced by S. cerevisiae. This study demonstrates that chemostat-based transcriptome analysis is a powerful tool to investigate microbial interactions in mixed populations. PMID:23872557

CONVERGENT TRANSCRIPTOMICS AND PROTEOMICS OF ENVIRONMENTAL ENRICHMENT AND COCAINE IDENTIFIES NOVEL THERAPEUTIC STRATEGIES FOR ADDICTION

PubMed Central

ZHANG, YAFANG; CROFTON, ELIZABETH J.; FAN, XIUZHEN; LI, DINGGE; KONG, FANPING; SINHA, MALA; LUXON, BRUCE A.; SPRATT, HEIDI M.; LICHTI, CHERYL F.; GREEN, THOMAS A.

2016-01-01

Transcriptomic and proteomic approaches have separately proven effective at identifying novel mechanisms affecting addiction-related behavior; however, it is difficult to prioritize the many promising leads from each approach. A convergent secondary analysis of proteomic and transcriptomic results can glean additional information to help prioritize promising leads. The current study is a secondary analysis of the convergence of recently published separate transcriptomic and proteomic analyses of nucleus accumbens (NAc) tissue from rats subjected to environmental enrichment vs. isolation and cocaine self-administration vs. saline. Multiple bioinformatics approaches (e.g. Gene Ontology (GO) analysis, Ingenuity Pathway Analysis (IPA), and Gene Set Enrichment Analysis (GSEA)) were used to interrogate these rich data sets. Although there was little correspondence between mRNA vs. protein at the individual target level, good correspondence was found at the level of gene/protein sets, particularly for the environmental enrichment manipulation. These data identify gene sets where there is a positive relationship between changes in mRNA and protein (e.g. glycolysis, ATP synthesis, translation elongation factor activity, etc.) and gene sets where there is an inverse relationship (e.g. ribosomes, Rho GTPase signaling, protein ubiquitination, etc.). Overall environmental enrichment produced better correspondence than cocaine self-administration. The individual targets contributing to mRNA and protein effects were largely not overlapping. As a whole, these results confirm that robust transcriptomic and proteomic data sets can provide similar results at the gene/protein set level even when there is little correspondence at the individual target level and little overlap in the targets contributing to the effects. PMID:27717806

Transcriptome-based characterization of interactions between Saccharomyces cerevisiae and Lactobacillus delbrueckii subsp. bulgaricus in lactose-grown chemostat cocultures.

PubMed

Mendes, Filipa; Sieuwerts, Sander; de Hulster, Erik; Almering, Marinka J H; Luttik, Marijke A H; Pronk, Jack T; Smid, Eddy J; Bron, Peter A; Daran-Lapujade, Pascale

2013-10-01

Mixed populations of Saccharomyces cerevisiae yeasts and lactic acid bacteria occur in many dairy, food, and beverage fermentations, but knowledge about their interactions is incomplete. In the present study, interactions between Saccharomyces cerevisiae and Lactobacillus delbrueckii subsp. bulgaricus, two microorganisms that co-occur in kefir fermentations, were studied during anaerobic growth on lactose. By combining physiological and transcriptome analysis of the two strains in the cocultures, five mechanisms of interaction were identified. (i) Lb. delbrueckii subsp. bulgaricus hydrolyzes lactose, which cannot be metabolized by S. cerevisiae, to galactose and glucose. Subsequently, galactose, which cannot be metabolized by Lb. delbrueckii subsp. bulgaricus, is excreted and provides a carbon source for yeast. (ii) In pure cultures, Lb. delbrueckii subsp. bulgaricus grows only in the presence of increased CO2 concentrations. In anaerobic mixed cultures, the yeast provides this CO2 via alcoholic fermentation. (iii) Analysis of amino acid consumption from the defined medium indicated that S. cerevisiae supplied alanine to the bacterium. (iv) A mild but significant low-iron response in the yeast transcriptome, identified by DNA microarray analysis, was consistent with the chelation of iron by the lactate produced by Lb. delbrueckii subsp. bulgaricus. (v) Transcriptome analysis of Lb. delbrueckii subsp. bulgaricus in mixed cultures showed an overrepresentation of transcripts involved in lipid metabolism, suggesting either a competition of the two microorganisms for fatty acids or a response to the ethanol produced by S. cerevisiae. This study demonstrates that chemostat-based transcriptome analysis is a powerful tool to investigate microbial interactions in mixed populations.

Microfluidic single-cell whole-transcriptome sequencing.

PubMed

Streets, Aaron M; Zhang, Xiannian; Cao, Chen; Pang, Yuhong; Wu, Xinglong; Xiong, Liang; Yang, Lu; Fu, Yusi; Zhao, Liang; Tang, Fuchou; Huang, Yanyi

2014-05-13

Single-cell whole-transcriptome analysis is a powerful tool for quantifying gene expression heterogeneity in populations of cells. Many techniques have, thus, been recently developed to perform transcriptome sequencing (RNA-Seq) on individual cells. To probe subtle biological variation between samples with limiting amounts of RNA, more precise and sensitive methods are still required. We adapted a previously developed strategy for single-cell RNA-Seq that has shown promise for superior sensitivity and implemented the chemistry in a microfluidic platform for single-cell whole-transcriptome analysis. In this approach, single cells are captured and lysed in a microfluidic device, where mRNAs with poly(A) tails are reverse-transcribed into cDNA. Double-stranded cDNA is then collected and sequenced using a next generation sequencing platform. We prepared 94 libraries consisting of single mouse embryonic cells and technical replicates of extracted RNA and thoroughly characterized the performance of this technology. Microfluidic implementation increased mRNA detection sensitivity as well as improved measurement precision compared with tube-based protocols. With 0.2 M reads per cell, we were able to reconstruct a majority of the bulk transcriptome with 10 single cells. We also quantified variation between and within different types of mouse embryonic cells and found that enhanced measurement precision, detection sensitivity, and experimental throughput aided the distinction between biological variability and technical noise. With this work, we validated the advantages of an early approach to single-cell RNA-Seq and showed that the benefits of combining microfluidic technology with high-throughput sequencing will be valuable for large-scale efforts in single-cell transcriptome analysis.

The protein expression landscape of mitosis and meiosis in diploid budding yeast.

PubMed

Becker, Emmanuelle; Com, Emmanuelle; Lavigne, Régis; Guilleux, Marie-Hélène; Evrard, Bertrand; Pineau, Charles; Primig, Michael

2017-03-06

Saccharomyces cerevisiae is an established model organism for the molecular analysis of fundamental biological processes. The genomes of numerous strains have been sequenced, and the transcriptome and proteome ofmajor phases during the haploid and diploid yeast life cycle have been determined. However, much less is known about dynamic changes of the proteome when cells switch from mitotic growth to meiotic development. We report a quantitative protein profiling analysis of yeast cell division and differentiation based on mass spectrometry. Information about protein levels was integrated with strand-specific tiling array expression data. We identified a total of 2366 proteins in at least one condition, including 175 proteins showing a statistically significant>5-fold change across the sample set, and 136 proteins detectable in sporulating but not respiring cells. We correlate protein expression patterns with biological processes and molecular function by Gene Ontology term enrichment, chemoprofiling, transcription interference and the formation of double stranded RNAs by overlapping sense/antisense transcripts. Our work provides initial quantitative insight into protein expression in diploid respiring and differentiating yeast cells. Critically, it associates developmentally regulated induction of antisense long noncoding RNAs and double stranded RNAs with fluctuating protein concentrations during growth and development. This integrated genomics analysis helps better understand how the transcriptome and the proteome correlate in diploid yeast cells undergoing mitotic growth in the presence of acetate (respiration) versus meiotic differentiation (Meiosis I and II). The study (i) provides quantitative expression data for 2366 proteins and their cognate mRNAs in at least one sample, (ii) shows strongly fluctuating protein levels during growth and differentiation for 175 cases, and (iii) identifies 136 proteins absent in mitotic but present in meiotic yeast cells. We have integrated protein profiling data using mass spectrometry with tiling array RNA profiling data and information on double-stranded RNAs (dsRNAs) by overlapping sense/antisense transcripts from an RNA-Sequencing experiment. This work therefore provides quantitative insight into protein expression during cell division and development and associates changing protein levels with developmental stage specific induction of antisense transcripts and the formation of dsRNAs. Copyright © 2017 Elsevier B.V. All rights reserved.

Genome-Scale Transcriptome Analysis in Response to Nitric Oxide in Birch Cells: Implications of the Triterpene Biosynthetic Pathway

PubMed Central

Zeng, Fansuo; Sun, Fengkun; Li, Leilei; Liu, Kun; Zhan, Yaguang

2014-01-01

Evidence supporting nitric oxide (NO) as a mediator of plant biochemistry continues to grow, but its functions at the molecular level remains poorly understood and, in some cases, controversial. To study the role of NO at the transcriptional level in Betula platyphylla cells, we conducted a genome-scale transcriptome analysis of these cells. The transcriptome of untreated birch cells and those treated by sodium nitroprusside (SNP) were analyzed using the Solexa sequencing. Data were collected by sequencing cDNA libraries of birch cells, which had a long period to adapt to the suspension culture conditions before SNP-treated cells and untreated cells were sampled. Among the 34,100 UniGenes detected, BLASTX search revealed that 20,631 genes showed significant (E-values≤10−5) sequence similarity with proteins from the NR-database. Numerous expressed sequence tags (i.e., 1374) were identified as differentially expressed between the 12 h SNP-treated cells and control cells samples: 403 up-regulated and 971 down-regulated. From this, we specifically examined a core set of NO-related transcripts. The altered expression levels of several transcripts, as determined by transcriptome analysis, was confirmed by qRT-PCR. The results of transcriptome analysis, gene expression quantification, the content of triterpenoid and activities of defensive enzymes elucidated NO has a significant effect on many processes including triterpenoid production, carbohydrate metabolism and cell wall biosynthesis. PMID:25551661

TRAM (Transcriptome Mapper): database-driven creation and analysis of transcriptome maps from multiple sources

PubMed Central

2011-01-01

Background Several tools have been developed to perform global gene expression profile data analysis, to search for specific chromosomal regions whose features meet defined criteria as well as to study neighbouring gene expression. However, most of these tools are tailored for a specific use in a particular context (e.g. they are species-specific, or limited to a particular data format) and they typically accept only gene lists as input. Results TRAM (Transcriptome Mapper) is a new general tool that allows the simple generation and analysis of quantitative transcriptome maps, starting from any source listing gene expression values for a given gene set (e.g. expression microarrays), implemented as a relational database. It includes a parser able to assign univocal and updated gene symbols to gene identifiers from different data sources. Moreover, TRAM is able to perform intra-sample and inter-sample data normalization, including an original variant of quantile normalization (scaled quantile), useful to normalize data from platforms with highly different numbers of investigated genes. When in 'Map' mode, the software generates a quantitative representation of the transcriptome of a sample (or of a pool of samples) and identifies if segments of defined lengths are over/under-expressed compared to the desired threshold. When in 'Cluster' mode, the software searches for a set of over/under-expressed consecutive genes. Statistical significance for all results is calculated with respect to genes localized on the same chromosome or to all genome genes. Transcriptome maps, showing differential expression between two sample groups, relative to two different biological conditions, may be easily generated. We present the results of a biological model test, based on a meta-analysis comparison between a sample pool of human CD34+ hematopoietic progenitor cells and a sample pool of megakaryocytic cells. Biologically relevant chromosomal segments and gene clusters with differential expression during the differentiation toward megakaryocyte were identified. Conclusions TRAM is designed to create, and statistically analyze, quantitative transcriptome maps, based on gene expression data from multiple sources. The release includes FileMaker Pro database management runtime application and it is freely available at http://apollo11.isto.unibo.it/software/, along with preconfigured implementations for mapping of human, mouse and zebrafish transcriptomes. PMID:21333005

First Transcriptome and Digital Gene Expression Analysis in Neuroptera with an Emphasis on Chemoreception Genes in Chrysopa pallens (Rambur).

PubMed

Li, Zhao-Qun; Zhang, Shuai; Ma, Yan; Luo, Jun-Yu; Wang, Chun-Yi; Lv, Li-Min; Dong, Shuang-Lin; Cui, Jin-Jie

2013-01-01

Chrysopa pallens (Rambur) are the most important natural enemies and predators of various agricultural pests. Understanding the sophisticated olfactory system in insect antennae is crucial for studying the physiological bases of olfaction and also could lead to effective applications of C. pallens in integrated pest management. However no transcriptome information is available for Neuroptera, and sequence data for C. pallens are scarce, so obtaining more sequence data is a priority for researchers on this species. To facilitate identifying sets of genes involved in olfaction, a normalized transcriptome of C. pallens was sequenced. A total of 104,603 contigs were obtained and assembled into 10,662 clusters and 39,734 singletons; 20,524 were annotated based on BLASTX analyses. A large number of candidate chemosensory genes were identified, including 14 odorant-binding proteins (OBPs), 22 chemosensory proteins (CSPs), 16 ionotropic receptors, 14 odorant receptors, and genes potentially involved in olfactory modulation. To better understand the OBPs, CSPs and cytochrome P450s, phylogenetic trees were constructed. In addition, 10 digital gene expression libraries of different tissues were constructed and gene expression profiles were compared among different tissues in males and females. Our results provide a basis for exploring the mechanisms of chemoreception in C. pallens, as well as other insects. The evolutionary analyses in our study provide new insights into the differentiation and evolution of insect OBPs and CSPs. Our study provided large-scale sequence information for further studies in C. pallens.

Fluxomics - connecting 'omics analysis and phenotypes.

PubMed

Winter, Gal; Krömer, Jens O

2013-07-01

In our modern 'omics era, metabolic flux analysis (fluxomics) represents the physiological counterpart of its siblings transcriptomics, proteomics and metabolomics. Fluxomics integrates in vivo measurements of metabolic fluxes with stoichiometric network models to allow the determination of absolute flux through large networks of the central carbon metabolism. There are many approaches to implement fluxomics including flux balance analysis (FBA), (13) C fluxomics and (13) C-constrained FBA as well as many experimental settings for flux measurement including dynamic, stationary and semi-stationary. Here we outline the principles of the different approaches and their relative advantages. We demonstrate the unique contribution of flux analysis for phenotype elucidation using a thoroughly studied metabolic reaction as a case study, the microbial aerobic/anaerobic shift, highlighting the importance of flux analysis as a single layer of data as well as interlaced in multi-omics studies. © 2012 John Wiley & Sons Ltd and Society for Applied Microbiology.

Integrating genome-wide association study and expression quantitative trait loci data identifies multiple genes and gene set associated with neuroticism.

PubMed

Fan, Qianrui; Wang, Wenyu; Hao, Jingcan; He, Awen; Wen, Yan; Guo, Xiong; Wu, Cuiyan; Ning, Yujie; Wang, Xi; Wang, Sen; Zhang, Feng

2017-08-01

Neuroticism is a fundamental personality trait with significant genetic determinant. To identify novel susceptibility genes for neuroticism, we conducted an integrative analysis of genomic and transcriptomic data of genome wide association study (GWAS) and expression quantitative trait locus (eQTL) study. GWAS summary data was driven from published studies of neuroticism, totally involving 170,906 subjects. eQTL dataset containing 927,753 eQTLs were obtained from an eQTL meta-analysis of 5311 samples. Integrative analysis of GWAS and eQTL data was conducted by summary data-based Mendelian randomization (SMR) analysis software. To identify neuroticism associated gene sets, the SMR analysis results were further subjected to gene set enrichment analysis (GSEA). The gene set annotation dataset (containing 13,311 annotated gene sets) of GSEA Molecular Signatures Database was used. SMR single gene analysis identified 6 significant genes for neuroticism, including MSRA (p value=2.27×10 -10 ), MGC57346 (p value=6.92×10 -7 ), BLK (p value=1.01×10 -6 ), XKR6 (p value=1.11×10 -6 ), C17ORF69 (p value=1.12×10 -6 ) and KIAA1267 (p value=4.00×10 -6 ). Gene set enrichment analysis observed significant association for Chr8p23 gene set (false discovery rate=0.033). Our results provide novel clues for the genetic mechanism studies of neuroticism. Copyright © 2017. Published by Elsevier Inc.

Comparative transcriptome analysis by RNAseq of necrotic enteritis Clostridium perfringens during in vivo colonization and in vitro conditions.

PubMed

Parreira, Valeria R; Russell, Kay; Athanasiadou, Spiridoula; Prescott, John F

2016-08-12

Necrotic enteritis (NE) caused by netB-positive type A Clostridium perfringens is an important bacterial disease of poultry. Through its complex regulatory system, C. perfringens orchestrates the expression of a collection of toxins and extracellular enzymes that are crucial for the development of the disease; environmental conditions play an important role in their regulation. In this study, and for the first time, global transcriptomic analysis was performed on ligated intestinal loops in chickens colonized with a netB-positive C. perfringens strain, as well as the same strain propagated in vitro under various nutritional and environmental conditions. Analysis of the respective pathogen transcriptomes revealed up to 673 genes that were significantly expressed in vivo. Gene expression profiles in vivo were most similar to those of C. perfringens grown in nutritionally-deprived conditions. Taken together, our results suggest a bacterial transcriptome responses to the early stages of adaptation, and colonization of, the chicken intestine. Our work also reveals how netB-positive C. perfringens reacts to different environmental conditions including those in the chicken intestine.

Comparative transcriptome analysis of unripe and mid-ripe fruit of Mangifera indica (var. “Dashehari”) unravels ripening associated genes

PubMed Central

Srivastava, Smriti; Singh, Rajesh K.; Pathak, Garima; Goel, Ridhi; Asif, Mehar Hasan; Sane, Aniruddha P.; Sane, Vidhu A.

2016-01-01

Ripening in mango is under a complex control of ethylene. In an effort to understand the complex spatio-temporal control of ripening we have made use of a popular N. Indian variety “Dashehari” This variety ripens from the stone inside towards the peel outside and forms jelly in the pulp in ripe fruits. Through a combination of 454 and Illumina sequencing, a transcriptomic analysis of gene expression from unripe and midripe stages have been performed in triplicates. Overall 74,312 unique transcripts with ≥1 FPKM were obtained. The transcripts related to 127 pathways were identified in “Dashehari” mango transcriptome by the KEGG analysis. These pathways ranged from detoxification, ethylene biosynthesis, carbon metabolism and aromatic amino acid degradation. The transcriptome study reveals differences not only in expression of softening associated genes but also those that govern ethylene biosynthesis and other nutritional characteristics. This study could help to develop ripening related markers for selective breeding to reduce the problems of excess jelly formation during softening in the “Dashehari” variety. PMID:27586495

Variability of Potassium Channel Blockers in Mesobuthus eupeus Scorpion Venom with Focus on Kv1.1: AN INTEGRATED TRANSCRIPTOMIC AND PROTEOMIC STUDY.

PubMed

Kuzmenkov, Alexey I; Vassilevski, Alexander A; Kudryashova, Kseniya S; Nekrasova, Oksana V; Peigneur, Steve; Tytgat, Jan; Feofanov, Alexey V; Kirpichnikov, Mikhail P; Grishin, Eugene V

2015-05-08

The lesser Asian scorpion Mesobuthus eupeus (Buthidae) is one of the most widely spread and dispersed species of the Mesobuthus genus, and its venom is actively studied. Nevertheless, a considerable amount of active compounds is still under-investigated due to the high complexity of this venom. Here, we report a comprehensive analysis of putative potassium channel toxins (KTxs) from the cDNA library of M. eupeus venom glands, and we compare the deduced KTx structures with peptides purified from the venom. For the transcriptome analysis, we used conventional tools as well as a search for structural motifs characteristic of scorpion venom components in the form of regular expressions. We found 59 candidate KTxs distributed in 30 subfamilies and presenting the cysteine-stabilized α/β and inhibitor cystine knot types of fold. M. eupeus venom was then separated to individual components by multistage chromatography. A facile fluorescent system based on the expression of the KcsA-Kv1.1 hybrid channels in Escherichia coli and utilization of a labeled scorpion toxin was elaborated and applied to follow Kv1.1 pore binding activity during venom separation. As a result, eight high affinity Kv1.1 channel blockers were identified, including five novel peptides, which extend the panel of potential pharmacologically important Kv1 ligands. Activity of the new peptides against rat Kv1.1 channel was confirmed (IC50 in the range of 1-780 nm) by the two-electrode voltage clamp technique using a standard Xenopus oocyte system. Our integrated approach is of general utility and efficiency to mine natural venoms for KTxs. © 2015 by The American Society for Biochemistry and Molecular Biology, Inc.

Prior knowledge-based approach for associating contaminants with biological effects: A case study in the St. Croix River basin, MN, WI, USA

USGS Publications Warehouse

Schroeder, Anthony L.; Martinovic-Weigelt, Dalma; Ankley, Gerald T.; Lee, Kathy E.; Garcia-Reyero, Natalia; Perkins, Edward J.; Schoenfuss, Heiko L.; Villeneuve, Daniel L.

2017-01-01

Evaluating potential adverse effects of complex chemical mixtures in the environment is challenging. One way to address that challenge is through more integrated analysis of chemical monitoring and biological effects data. In the present study, water samples from five locations near two municipal wastewater treatment plants in the St. Croix River basin, on the border of MN and WI, USA, were analyzed for 127 organic contaminants. Known chemical-gene interactions were used to develop site-specific knowledge assembly models (KAMs) and formulate hypotheses concerning possible biological effects associated with chemicals detected in water samples from each location. Additionally, hepatic gene expression data were collected for fathead minnows (Pimephales promelas) exposed in situ, for 12 d, at each location. Expression data from oligonucleotide microarrays were analyzed to identify functional annotation terms enriched among the differentially-expressed probes. The general nature of many of the terms made hypothesis formulation on the basis of the transcriptome-level response alone difficult. However, integrated analysis of the transcriptome data in the context of the site-specific KAMs allowed for evaluation of the likelihood of specific chemicals contributing to observed biological responses. Thirteen chemicals (atrazine, carbamazepine, metformin, thiabendazole, diazepam, cholesterol, p-cresol, phenytoin, omeprazole, ethyromycin, 17β-estradiol, cimetidine, and estrone), for which there was statistically significant concordance between occurrence at a site and expected biological response as represented in the KAM, were identified. While not definitive, the approach provides a line of evidence for evaluating potential cause-effect relationships between components of a complex mixture of contaminants and biological effects data, which can inform subsequent monitoring and investigation.

Prior knowledge-based approach for associating contaminants with biological effects: A case study in the St. Croix River basin, MN, WI, USA.

PubMed

Schroeder, Anthony L; Martinović-Weigelt, Dalma; Ankley, Gerald T; Lee, Kathy E; Garcia-Reyero, Natalia; Perkins, Edward J; Schoenfuss, Heiko L; Villeneuve, Daniel L

2017-02-01

Evaluating potential adverse effects of complex chemical mixtures in the environment is challenging. One way to address that challenge is through more integrated analysis of chemical monitoring and biological effects data. In the present study, water samples from five locations near two municipal wastewater treatment plants in the St. Croix River basin, on the border of MN and WI, USA, were analyzed for 127 organic contaminants. Known chemical-gene interactions were used to develop site-specific knowledge assembly models (KAMs) and formulate hypotheses concerning possible biological effects associated with chemicals detected in water samples from each location. Additionally, hepatic gene expression data were collected for fathead minnows (Pimephales promelas) exposed in situ, for 12 d, at each location. Expression data from oligonucleotide microarrays were analyzed to identify functional annotation terms enriched among the differentially-expressed probes. The general nature of many of the terms made hypothesis formulation on the basis of the transcriptome-level response alone difficult. However, integrated analysis of the transcriptome data in the context of the site-specific KAMs allowed for evaluation of the likelihood of specific chemicals contributing to observed biological responses. Thirteen chemicals (atrazine, carbamazepine, metformin, thiabendazole, diazepam, cholesterol, p-cresol, phenytoin, omeprazole, ethyromycin, 17β-estradiol, cimetidine, and estrone), for which there was statistically significant concordance between occurrence at a site and expected biological response as represented in the KAM, were identified. While not definitive, the approach provides a line of evidence for evaluating potential cause-effect relationships between components of a complex mixture of contaminants and biological effects data, which can inform subsequent monitoring and investigation. Published by Elsevier Ltd.

Integrated “omics” profiling indicates that miRNAs are modulators of the ontogenetic venom composition shift in the Central American rattlesnake, Crotalus simus simus

PubMed Central

2013-01-01

Background Understanding the processes that drive the evolution of snake venom is a topic of great research interest in molecular and evolutionary toxinology. Recent studies suggest that ontogenetic changes in venom composition are genetically controlled rather than environmentally induced. However, the molecular mechanisms underlying these changes remain elusive. Here we have explored the basis and level of regulation of the ontogenetic shift in the venom composition of the Central American rattlesnake, Crotalus s. simus using a combined proteomics and transcriptomics approach. Results Proteomic analysis showed that the ontogenetic shift in the venom composition of C. s. simus is essentially characterized by a gradual reduction in the expression of serine proteinases and PLA2 molecules, particularly crotoxin, a β-neurotoxic heterodimeric PLA2, concominantly with an increment of PI and PIII metalloproteinases at age 9–18 months. Comparison of the transcriptional activity of the venom glands of neonate and adult C. s. simus specimens indicated that their transcriptomes exhibit indistinguisable toxin family profiles, suggesting that the elusive mechanism by which shared transcriptomes generate divergent venom phenotypes may operate post-transcriptionally. Specifically, miRNAs with frequency count of 1000 or greater exhibited an uneven distribution between the newborn and adult datasets. Of note, 590 copies of a miRNA targeting crotoxin B-subunit was exclusively found in the transcriptome of the adult snake, whereas 1185 copies of a miRNA complementary to a PIII-SVMP mRNA was uniquely present in the newborn dataset. These results support the view that age-dependent changes in the concentration of miRNA modulating the transition from a crotoxin-rich to a SVMP-rich venom from birth through adulhood can potentially explain what is observed in the proteomic analysis of the ontogenetic changes in the venom composition of C. s. simus. Conclusions Existing snake venom toxins are the result of early recruitment events in the Toxicofera clade of reptiles by which ordinary genes were duplicated, and the new genes selectively expressed in the venom gland and amplified to multigene families with extensive neofunctionalization throughout the approximately 112–125 million years of ophidian evolution. Our findings support the view that understanding the phenotypic diversity of snake venoms requires a deep knowledge of the mechanisms regulating the transcriptional and translational activity of the venom gland. Our results suggest a functional role for miRNAs. The impact of specific miRNAs in the modulation of venom composition, and the integration of the mechanisms responsible for the generation of these miRNAs in the evolutionary landscape of the snake's venom gland, are further challenges for future research. PMID:23575160

The Air Force In Silico -- Computational Biology in 2025

DTIC Science & Technology

2007-11-01

and chromosome) these new fields are commonly referred to as “~omics.” Proteomics , transcriptomics, metabolomics , epigenomics, physiomics... Bioinformatics , 2006, http://journal.imbio.de/ http://www-bm.ipk-gatersleben.de/stable/php/ journal /articles/pdf/jib-22.pdf (accessed 30 September...Chirino, G. Tansley and I. Dryden, “The implications for Bioinformatics of integration across physical scales,” Journal of Integrative Bioinformatics

Ontology-based, Tissue MicroArray oriented, image centered tissue bank

PubMed Central

Viti, Federica; Merelli, Ivan; Caprera, Andrea; Lazzari, Barbara; Stella, Alessandra; Milanesi, Luciano

2008-01-01

Background Tissue MicroArray technique is becoming increasingly important in pathology for the validation of experimental data from transcriptomic analysis. This approach produces many images which need to be properly managed, if possible with an infrastructure able to support tissue sharing between institutes. Moreover, the available frameworks oriented to Tissue MicroArray provide good storage for clinical patient, sample treatment and block construction information, but their utility is limited by the lack of data integration with biomolecular information. Results In this work we propose a Tissue MicroArray web oriented system to support researchers in managing bio-samples and, through the use of ontologies, enables tissue sharing aimed at the design of Tissue MicroArray experiments and results evaluation. Indeed, our system provides ontological description both for pre-analysis tissue images and for post-process analysis image results, which is crucial for information exchange. Moreover, working on well-defined terms it is then possible to query web resources for literature articles to integrate both pathology and bioinformatics data. Conclusions Using this system, users associate an ontology-based description to each image uploaded into the database and also integrate results with the ontological description of biosequences identified in every tissue. Moreover, it is possible to integrate the ontological description provided by the user with a full compliant gene ontology definition, enabling statistical studies about correlation between the analyzed pathology and the most commonly related biological processes. PMID:18460177

Brownian model of transcriptome evolution and phylogenetic network visualization between tissues.

PubMed

Gu, Xun; Ruan, Hang; Su, Zhixi; Zou, Yangyun

2017-09-01

While phylogenetic analysis of transcriptomes of the same tissue is usually congruent with the species tree, the controversy emerges when multiple tissues are included, that is, whether species from the same tissue are clustered together, or different tissues from the same species are clustered together. Recent studies have suggested that phylogenetic network approach may shed some lights on our understanding of multi-tissue transcriptome evolution; yet the underlying evolutionary mechanism remains unclear. In this paper we develop a Brownian-based model of transcriptome evolution under the phylogenetic network that can statistically distinguish between the patterns of species-clustering and tissue-clustering. Our model can be used as a null hypothesis (neutral transcriptome evolution) for testing any correlation in tissue evolution, can be applied to cancer transcriptome evolution to study whether two tumors of an individual appeared independently or via metastasis, and can be useful to detect convergent evolution at the transcriptional level. Copyright © 2017. Published by Elsevier Inc.

Transcriptomic Studies of the Effect of nod Gene-Inducing Molecules in Rhizobia: Different Weapons, One Purpose

PubMed Central

Jiménez-Guerrero, Irene; Acosta-Jurado, Sebastián; Navarro-Gómez, Pilar; López-Baena, Francisco Javier; Ollero, Francisco Javier

2017-01-01

Simultaneous quantification of transcripts of the whole bacterial genome allows the analysis of the global transcriptional response under changing conditions. RNA-seq and microarrays are the most used techniques to measure these transcriptomic changes, and both complement each other in transcriptome profiling. In this review, we exhaustively compiled the symbiosis-related transcriptomic reports (microarrays and RNA sequencing) carried out hitherto in rhizobia. This review is specially focused on transcriptomic changes that takes place when five rhizobial species, Bradyrhizobium japonicum (=diazoefficiens) USDA 110, Rhizobium leguminosarum biovar viciae 3841, Rhizobium tropici CIAT 899, Sinorhizobium (=Ensifer) meliloti 1021 and S. fredii HH103, recognize inducing flavonoids, plant-exuded phenolic compounds that activate the biosynthesis and export of Nod factors (NF) in all analysed rhizobia. Interestingly, our global transcriptomic comparison also indicates that each rhizobial species possesses its own arsenal of molecular weapons accompanying the set of NF in order to establish a successful interaction with host legumes. PMID:29267254

Analysis of Bos taurus and Sus scrofa X and Y chromosome transcriptome highlights reproductive driver genes

PubMed Central

Khan, Faheem Ahmed; Liu, Hui; Zhou, Hao; Wang, Kai; Qamar, Muhammad Tahir Ul; Pandupuspitasari, Nuruliarizki Shinta; Shujun, Zhang

2017-01-01

The biology of sperm, its capability of fertilizing an egg and its role in sex ratio are the major biological questions in reproductive biology. To answer these question we integrated X and Y chromosome transcriptome across different species: Bos taurus and Sus scrofa and identified reproductive driver genes based on Weighted Gene Co-Expression Network Analysis (WGCNA) algorithm. Our strategy resulted in 11007 and 10445 unique genes consisting of 9 and 11 reproductive modules in Bos taurus and Sus scrofa, respectively. The consensus module calculation yields an overall 167 overlapped genes which were mapped to 846 DEGs in Bos taurus to finally get a list of 67 dual feature genes. We develop gene co-expression network of selected 67 genes that consists of 58 nodes (27 down-regulated and 31 up-regulated genes) enriched to 66 GO biological process (BP) including 6 GO annotations related to reproduction and two KEGG pathways. Moreover, we searched significantly related TF (ISRE, AP1FJ, RP58, CREL) and miRNAs (bta-miR-181a, bta-miR-17-5p, bta-miR-146b, bta-miR-146a) which targeted the genes in co-expression network. In addition we performed genetic analysis including phylogenetic, functional domain identification, epigenetic modifications, mutation analysis of the most important reproductive driver genes PRM1, PPP2R2B and PAFAH1B1 and finally performed a protein docking analysis to visualize their therapeutic and gene expression regulation ability. PMID:28903352

Toxicogenomics concepts and applications to study hepatic effects of food additives and chemicals

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stierum, Rob; Heijne, Wilbert; Kienhuis, Anne

2005-09-01

Transcriptomics, proteomics and metabolomics are genomics technologies with great potential in toxicological sciences. Toxicogenomics involves the integration of conventional toxicological examinations with gene, protein or metabolite expression profiles. An overview together with selected examples of the possibilities of genomics in toxicology is given. The expectations raised by toxicogenomics are earlier and more sensitive detection of toxicity. Furthermore, toxicogenomics will provide a better understanding of the mechanism of toxicity and may facilitate the prediction of toxicity of unknown compounds. Mechanism-based markers of toxicity can be discovered and improved interspecies and in vitro-in vivo extrapolations will drive model developments in toxicology. Toxicologicalmore » assessment of chemical mixtures will benefit from the new molecular biological tools. In our laboratory, toxicogenomics is predominantly applied for elucidation of mechanisms of action and discovery of novel pathway-supported mechanism-based markers of liver toxicity. In addition, we aim to integrate transcriptome, proteome and metabolome data, supported by bioinformatics to develop a systems biology approach for toxicology. Transcriptomics and proteomics studies on bromobenzene-mediated hepatotoxicity in the rat are discussed. Finally, an example is shown in which gene expression profiling together with conventional biochemistry led to the discovery of novel markers for the hepatic effects of the food additives butylated hydroxytoluene, curcumin, propyl gallate and thiabendazole.« less

RNA-seq Transcriptome Analysis of Panax japonicus, and Its Comparison with Other Panax Species to Identify Potential Genes Involved in the Saponins Biosynthesis

PubMed Central

Rai, Amit; Yamazaki, Mami; Takahashi, Hiroki; Nakamura, Michimi; Kojoma, Mareshige; Suzuki, Hideyuki; Saito, Kazuki

2016-01-01

The Panax genus has been a source of natural medicine, benefitting human health over the ages, among which the Panax japonicus represents an important species. Our understanding of several key pathways and enzymes involved in the biosynthesis of ginsenosides, a pharmacologically active class of metabolites and a major chemical constituents of the rhizome extracts from the Panax species, are limited. Limited genomic information, and lack of studies on comparative transcriptomics across the Panax species have restricted our understanding of the biosynthetic mechanisms of these and many other important classes of phytochemicals. Herein, we describe Illumina based RNA sequencing analysis to characterize the transcriptome and expression profiles of genes expressed in the five tissues of P. japonicus, and its comparison with other Panax species. RNA sequencing and de novo transcriptome assembly for P. japonicus resulted in a total of 135,235 unigenes with 78,794 (58.24%) unigenes being annotated using NCBI-nr database. Transcriptome profiling, and gene ontology enrichment analysis for five tissues of P. japonicus showed that although overall processes were evenly conserved across all tissues. However, each tissue was characterized by several unique unigenes with the leaves showing the most unique unigenes among the tissues studied. A comparative analysis of the P. japonicus transcriptome assembly with publically available transcripts from other Panax species, namely, P. ginseng, P. notoginseng, and P. quinquefolius also displayed high sequence similarity across all Panax species, with P. japonicus showing highest similarity with P. ginseng. Annotation of P. japonicus transcriptome resulted in the identification of putative genes encoding all enzymes from the triterpene backbone biosynthetic pathways, and identified 24 and 48 unigenes annotated as cytochrome P450 (CYP) and glycosyltransferases (GT), respectively. These CYPs and GTs annotated unigenes were conserved across all Panax species and co-expressed with other the transcripts involved in the triterpenoid backbone biosynthesis pathways. Unigenes identified in this study represent strong candidates for being involved in the triterpenoid saponins biosynthesis, and can serve as a basis for future validation studies. PMID:27148308

Transcriptomic analysis of Arabidopsis developing stems: a close-up on cell wall genes

PubMed Central

Minic, Zoran; Jamet, Elisabeth; San-Clemente, Hélène; Pelletier, Sandra; Renou, Jean-Pierre; Rihouey, Christophe; Okinyo, Denis PO; Proux, Caroline; Lerouge, Patrice; Jouanin, Lise

2009-01-01

Background Different strategies (genetics, biochemistry, and proteomics) can be used to study proteins involved in cell biogenesis. The availability of the complete sequences of several plant genomes allowed the development of transcriptomic studies. Although the expression patterns of some Arabidopsis thaliana genes involved in cell wall biogenesis were identified at different physiological stages, detailed microarray analysis of plant cell wall genes has not been performed on any plant tissues. Using transcriptomic and bioinformatic tools, we studied the regulation of cell wall genes in Arabidopsis stems, i.e. genes encoding proteins involved in cell wall biogenesis and genes encoding secreted proteins. Results Transcriptomic analyses of stems were performed at three different developmental stages, i.e., young stems, intermediate stage, and mature stems. Many genes involved in the synthesis of cell wall components such as polysaccharides and monolignols were identified. A total of 345 genes encoding predicted secreted proteins with moderate or high level of transcripts were analyzed in details. The encoded proteins were distributed into 8 classes, based on the presence of predicted functional domains. Proteins acting on carbohydrates and proteins of unknown function constituted the two most abundant classes. Other proteins were proteases, oxido-reductases, proteins with interacting domains, proteins involved in signalling, and structural proteins. Particularly high levels of expression were established for genes encoding pectin methylesterases, germin-like proteins, arabinogalactan proteins, fasciclin-like arabinogalactan proteins, and structural proteins. Finally, the results of this transcriptomic analyses were compared with those obtained through a cell wall proteomic analysis from the same material. Only a small proportion of genes identified by previous proteomic analyses were identified by transcriptomics. Conversely, only a few proteins encoded by genes having moderate or high level of transcripts were identified by proteomics. Conclusion Analysis of the genes predicted to encode cell wall proteins revealed that about 345 genes had moderate or high levels of transcripts. Among them, we identified many new genes possibly involved in cell wall biogenesis. The discrepancies observed between results of this transcriptomic study and a previous proteomic study on the same material revealed post-transcriptional mechanisms of regulation of expression of genes encoding cell wall proteins. PMID:19149885

The Landscape of long non-coding RNA classification

PubMed Central

St Laurent, Georges; Wahlestedt, Claes; Kapranov, Philipp

2015-01-01

Advances in the depth and quality of transcriptome sequencing have revealed many new classes of long non-coding RNAs (lncRNAs). lncRNA classification has mushroomed to accommodate these new findings, even though the real dimensions and complexity of the non-coding transcriptome remain unknown. Although evidence of functionality of specific lncRNAs continues to accumulate, conflicting, confusing, and overlapping terminology has fostered ambiguity and lack of clarity in the field in general. The lack of fundamental conceptual un-ambiguous classification framework results in a number of challenges in the annotation and interpretation of non-coding transcriptome data. It also might undermine integration of the new genomic methods and datasets in an effort to unravel function of lncRNA. Here, we review existing lncRNA classifications, nomenclature, and terminology. Then we describe the conceptual guidelines that have emerged for their classification and functional annotation based on expanding and more comprehensive use of large systems biology-based datasets. PMID:25869999

The First Chameleon Transcriptome: Comparative Genomic Analysis of the OXPHOS System Reveals Loss of COX8 in Iguanian Lizards

PubMed Central

Bar-Yaacov, Dan; Bouskila, Amos; Mishmar, Dan

2013-01-01

Recently, we found dramatic mitochondrial DNA divergence of Israeli Chamaeleo chamaeleon populations into two geographically distinct groups. We aimed to examine whether the same pattern of divergence could be found in nuclear genes. However, no genomic resource is available for any chameleon species. Here we present the first chameleon transcriptome, obtained using deep sequencing (SOLiD). Our analysis identified 164,000 sequence contigs of which 19,000 yielded unique BlastX hits. To test the efficacy of our sequencing effort, we examined whether the chameleon and other available reptilian transcriptomes harbored complete sets of genes comprising known biochemical pathways, focusing on the nDNA-encoded oxidative phosphorylation (OXPHOS) genes as a model. As a reference for the screen, we used the human 86 (including isoforms) known structural nDNA-encoded OXPHOS subunits. Analysis of 34 publicly available vertebrate transcriptomes revealed orthologs for most human OXPHOS genes. However, OXPHOS subunit COX8 (Cytochrome C oxidase subunit 8), including all its known isoforms, was consistently absent in transcriptomes of iguanian lizards, implying loss of this subunit during the radiation of this suborder. The lack of COX8 in the suborder Iguania is intriguing, since it is important for cellular respiration and ATP production. Our sequencing effort added a new resource for comparative genomic studies, and shed new light on the evolutionary dynamics of the OXPHOS system. PMID:24009133

The first Chameleon transcriptome: comparative genomic analysis of the OXPHOS system reveals loss of COX8 in Iguanian lizards.

PubMed

Bar-Yaacov, Dan; Bouskila, Amos; Mishmar, Dan

2013-01-01

Recently, we found dramatic mitochondrial DNA divergence of Israeli Chamaeleo chamaeleon populations into two geographically distinct groups. We aimed to examine whether the same pattern of divergence could be found in nuclear genes. However, no genomic resource is available for any chameleon species. Here we present the first chameleon transcriptome, obtained using deep sequencing (SOLiD). Our analysis identified 164,000 sequence contigs of which 19,000 yielded unique BlastX hits. To test the efficacy of our sequencing effort, we examined whether the chameleon and other available reptilian transcriptomes harbored complete sets of genes comprising known biochemical pathways, focusing on the nDNA-encoded oxidative phosphorylation (OXPHOS) genes as a model. As a reference for the screen, we used the human 86 (including isoforms) known structural nDNA-encoded OXPHOS subunits. Analysis of 34 publicly available vertebrate transcriptomes revealed orthologs for most human OXPHOS genes. However, OXPHOS subunit COX8 (Cytochrome C oxidase subunit 8), including all its known isoforms, was consistently absent in transcriptomes of iguanian lizards, implying loss of this subunit during the radiation of this suborder. The lack of COX8 in the suborder Iguania is intriguing, since it is important for cellular respiration and ATP production. Our sequencing effort added a new resource for comparative genomic studies, and shed new light on the evolutionary dynamics of the OXPHOS system.

Aging-like Changes in the Transcriptome of Irradiated Microglia

PubMed Central

Li, Matthew D.; Burns, Terry C.; Kumar, Sunny; Morgan, Alexander A.; Sloan, Steven A.; Palmer, Theo D.

2014-01-01

Whole brain irradiation remains important in the management of brain tumors. Although necessary for improving survival outcomes, cranial irradiation also results in cognitive decline in long-term survivors. A chronic inflammatory state characterized by microglial activation has been implicated in radiation-induced brain injury. We here provide the first comprehensive transcriptional profile of irradiated microglia. Fluorescence-activated cell sorting (FACS) was used to isolate CD11b+ microglia from the hippocampi of C57BL/6 and Balb/c mice 1 month after 10Gy cranial irradiation. Affymetrix gene expression profiles were evaluated using linear modeling, rank product analyses. One month after irradiation, a conserved irradiation signature across strains was identified, comprising 448 and 85 differentially up- and down-regulated genes, respectively. Gene set enrichment analysis (GSEA) demonstrated enrichment for inflammation, including M1 macrophage-associated genes, but also an unexpected enrichment for extracellular matrix and blood coagulation-related gene sets, in contrast previously described microglial states. Weighted gene co-expression network analysis (WGCNA) confirmed these findings and further revealed alterations in mitochondrial function. The RNA-seq transcriptome of microglia 24h post-radiation proved similar to the 1-month transcriptome, but additionally featured alterations in apoptotic and lysosomal gene expression. Re-analysis of published aging mouse microglia transcriptome data demonstrated striking similarity to the 1 month irradiated microglia transcriptome, suggesting that shared mechanisms may underlie aging and chronic irradiation-induced cognitive decline. PMID:25690519

Use of prior knowledge for the analysis of high-throughput transcriptomics and metabolomics data

PubMed Central

2014-01-01

Background High-throughput omics technologies have enabled the measurement of many genes or metabolites simultaneously. The resulting high dimensional experimental data poses significant challenges to transcriptomics and metabolomics data analysis methods, which may lead to spurious instead of biologically relevant results. One strategy to improve the results is the incorporation of prior biological knowledge in the analysis. This strategy is used to reduce the solution space and/or to focus the analysis on biological meaningful regions. In this article, we review a selection of these methods used in transcriptomics and metabolomics. We combine the reviewed methods in three groups based on the underlying mathematical model: exploratory methods, supervised methods and estimation of the covariance matrix. We discuss which prior knowledge has been used, how it is incorporated and how it modifies the mathematical properties of the underlying methods. PMID:25033193

Integrative analysis of the Caenorhabditis elegans genome by the modENCODE project.

PubMed

Gerstein, Mark B; Lu, Zhi John; Van Nostrand, Eric L; Cheng, Chao; Arshinoff, Bradley I; Liu, Tao; Yip, Kevin Y; Robilotto, Rebecca; Rechtsteiner, Andreas; Ikegami, Kohta; Alves, Pedro; Chateigner, Aurelien; Perry, Marc; Morris, Mitzi; Auerbach, Raymond K; Feng, Xin; Leng, Jing; Vielle, Anne; Niu, Wei; Rhrissorrakrai, Kahn; Agarwal, Ashish; Alexander, Roger P; Barber, Galt; Brdlik, Cathleen M; Brennan, Jennifer; Brouillet, Jeremy Jean; Carr, Adrian; Cheung, Ming-Sin; Clawson, Hiram; Contrino, Sergio; Dannenberg, Luke O; Dernburg, Abby F; Desai, Arshad; Dick, Lindsay; Dosé, Andréa C; Du, Jiang; Egelhofer, Thea; Ercan, Sevinc; Euskirchen, Ghia; Ewing, Brent; Feingold, Elise A; Gassmann, Reto; Good, Peter J; Green, Phil; Gullier, Francois; Gutwein, Michelle; Guyer, Mark S; Habegger, Lukas; Han, Ting; Henikoff, Jorja G; Henz, Stefan R; Hinrichs, Angie; Holster, Heather; Hyman, Tony; Iniguez, A Leo; Janette, Judith; Jensen, Morten; Kato, Masaomi; Kent, W James; Kephart, Ellen; Khivansara, Vishal; Khurana, Ekta; Kim, John K; Kolasinska-Zwierz, Paulina; Lai, Eric C; Latorre, Isabel; Leahey, Amber; Lewis, Suzanna; Lloyd, Paul; Lochovsky, Lucas; Lowdon, Rebecca F; Lubling, Yaniv; Lyne, Rachel; MacCoss, Michael; Mackowiak, Sebastian D; Mangone, Marco; McKay, Sheldon; Mecenas, Desirea; Merrihew, Gennifer; Miller, David M; Muroyama, Andrew; Murray, John I; Ooi, Siew-Loon; Pham, Hoang; Phippen, Taryn; Preston, Elicia A; Rajewsky, Nikolaus; Rätsch, Gunnar; Rosenbaum, Heidi; Rozowsky, Joel; Rutherford, Kim; Ruzanov, Peter; Sarov, Mihail; Sasidharan, Rajkumar; Sboner, Andrea; Scheid, Paul; Segal, Eran; Shin, Hyunjin; Shou, Chong; Slack, Frank J; Slightam, Cindie; Smith, Richard; Spencer, William C; Stinson, E O; Taing, Scott; Takasaki, Teruaki; Vafeados, Dionne; Voronina, Ksenia; Wang, Guilin; Washington, Nicole L; Whittle, Christina M; Wu, Beijing; Yan, Koon-Kiu; Zeller, Georg; Zha, Zheng; Zhong, Mei; Zhou, Xingliang; Ahringer, Julie; Strome, Susan; Gunsalus, Kristin C; Micklem, Gos; Liu, X Shirley; Reinke, Valerie; Kim, Stuart K; Hillier, LaDeana W; Henikoff, Steven; Piano, Fabio; Snyder, Michael; Stein, Lincoln; Lieb, Jason D; Waterston, Robert H

2010-12-24

We systematically generated large-scale data sets to improve genome annotation for the nematode Caenorhabditis elegans, a key model organism. These data sets include transcriptome profiling across a developmental time course, genome-wide identification of transcription factor-binding sites, and maps of chromatin organization. From this, we created more complete and accurate gene models, including alternative splice forms and candidate noncoding RNAs. We constructed hierarchical networks of transcription factor-binding and microRNA interactions and discovered chromosomal locations bound by an unusually large number of transcription factors. Different patterns of chromatin composition and histone modification were revealed between chromosome arms and centers, with similarly prominent differences between autosomes and the X chromosome. Integrating data types, we built statistical models relating chromatin, transcription factor binding, and gene expression. Overall, our analyses ascribed putative functions to most of the conserved genome.

Unraveling snake venom complexity with 'omics' approaches: challenges and perspectives.

PubMed

Zelanis, André; Tashima, Alexandre Keiji

2014-09-01

The study of snake venom proteomes (venomics) has been experiencing a burst of reports, however the comprehensive knowledge of the dynamic range of proteins present within a single venom, the set of post-translational modifications (PTMs) as well as the lack of a comprehensive database related to venom proteins are among the main challenges in venomics research. The phenotypic plasticity in snake venom proteomes together with their inherent toxin proteoform diversity, points out to the use of integrative analysis in order to better understand their actual complexity. In this regard, such a systems venomics task should encompass the integration of data from transcriptomic and proteomic studies (specially the venom gland proteome), the identification of biological PTMs, and the estimation of artifactual proteomes and peptidomes generated by sample handling procedures. Copyright © 2014 Elsevier Ltd. All rights reserved.

Use of homologous and heterologous gene expression profiling tools to characterize transcription dynamics during apple fruit maturation and ripening.

PubMed

Costa, Fabrizio; Alba, Rob; Schouten, Henk; Soglio, Valeria; Gianfranceschi, Luca; Serra, Sara; Musacchi, Stefano; Sansavini, Silviero; Costa, Guglielmo; Fei, Zhangjun; Giovannoni, James

2010-10-25

Fruit development, maturation and ripening consists of a complex series of biochemical and physiological changes that in climacteric fruits, including apple and tomato, are coordinated by the gaseous hormone ethylene. These changes lead to final fruit quality and understanding of the functional machinery underlying these processes is of both biological and practical importance. To date many reports have been made on the analysis of gene expression in apple. In this study we focused our investigation on the role of ethylene during apple maturation, specifically comparing transcriptomics of normal ripening with changes resulting from application of the hormone receptor competitor 1-methylcyclopropene. To gain insight into the molecular process regulating ripening in apple, and to compare to tomato (model species for ripening studies), we utilized both homologous and heterologous (tomato) microarray to profile transcriptome dynamics of genes involved in fruit development and ripening, emphasizing those which are ethylene regulated.The use of both types of microarrays facilitated transcriptome comparison between apple and tomato (for the later using data previously published and available at the TED: tomato expression database) and highlighted genes conserved during ripening of both species, which in turn represent a foundation for further comparative genomic studies. The cross-species analysis had the secondary aim of examining the efficiency of heterologous (specifically tomato) microarray hybridization for candidate gene identification as related to the ripening process. The resulting transcriptomics data revealed coordinated gene expression during fruit ripening of a subset of ripening-related and ethylene responsive genes, further facilitating the analysis of ethylene response during fruit maturation and ripening. Our combined strategy based on microarray hybridization enabled transcriptome characterization during normal climacteric apple ripening, as well as definition of ethylene-dependent transcriptome changes. Comparison with tomato fruit maturation and ethylene responsive transcriptome activity facilitated identification of putative conserved orthologous ripening-related genes, which serve as an initial set of candidates for assessing conservation of gene activity across genomes of fruit bearing plant species.

Transcriptomic analysis of flower development in tea (Camellia sinensis (L.)).

PubMed

Liu, Feng; Wang, Yu; Ding, Zhaotang; Zhao, Lei; Xiao, Jun; Wang, Linjun; Ding, Shibo

2017-10-05

Flowering is a critical and complicated process in plant development, involving interactions of numerous endogenous and environmental factors, but little is known about the complex network regulating flower development in tea plants. In this study, de novo transcriptome assembly and gene expression analysis using Illumina sequencing technology were performed. Transcriptomic analysis assembles gene-related information involved in reproductive growth of C. sinensis. Gene Ontology (GO) analysis of the annotated unigenes revealed that the majority of sequenced genes were associated with metabolic and cellular processes, cell and cell parts, catalytic activity and binding. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis indicated that metabolic pathways, biosynthesis of secondary metabolites, and plant hormone signal transduction were enriched among the DEGs. Furthermore, 207 flowering-associated unigenes were identified from our database. Some transcription factors, such as WRKY, ERF, bHLH, MYB and MADS-box were shown to be up-regulated in floral transition, which might play the role of progression of flowering. Furthermore, 14 genes were selected for confirmation of expression levels using quantitative real-time PCR (qRT-PCR). The comprehensive transcriptomic analysis presents fundamental information on the genes and pathways which are involved in flower development in C. sinensis. Our data also provided a useful database for further research of tea and other species of plants. Copyright © 2017 Elsevier B.V. All rights reserved.

Microarray-Based Gene Expression Analysis for Veterinary Pathologists: A Review.

PubMed

Raddatz, Barbara B; Spitzbarth, Ingo; Matheis, Katja A; Kalkuhl, Arno; Deschl, Ulrich; Baumgärtner, Wolfgang; Ulrich, Reiner

2017-09-01

High-throughput, genome-wide transcriptome analysis is now commonly used in all fields of life science research and is on the cusp of medical and veterinary diagnostic application. Transcriptomic methods such as microarrays and next-generation sequencing generate enormous amounts of data. The pathogenetic expertise acquired from understanding of general pathology provides veterinary pathologists with a profound background, which is essential in translating transcriptomic data into meaningful biological knowledge, thereby leading to a better understanding of underlying disease mechanisms. The scientific literature concerning high-throughput data-mining techniques usually addresses mathematicians or computer scientists as the target audience. In contrast, the present review provides the reader with a clear and systematic basis from a veterinary pathologist's perspective. Therefore, the aims are (1) to introduce the reader to the necessary methodological background; (2) to introduce the sequential steps commonly performed in a microarray analysis including quality control, annotation, normalization, selection of differentially expressed genes, clustering, gene ontology and pathway analysis, analysis of manually selected genes, and biomarker discovery; and (3) to provide references to publically available and user-friendly software suites. In summary, the data analysis methods presented within this review will enable veterinary pathologists to analyze high-throughput transcriptome data obtained from their own experiments, supplemental data that accompany scientific publications, or public repositories in order to obtain a more in-depth insight into underlying disease mechanisms.

De novo assembling and primary analysis of genome and transcriptome of gray whale Eschrichtius robustus.

PubMed

Moskalev, Alexey А; Kudryavtseva, Anna V; Graphodatsky, Alexander S; Beklemisheva, Violetta R; Serdyukova, Natalya A; Krutovsky, Konstantin V; Sharov, Vadim V; Kulakovskiy, Ivan V; Lando, Andrey S; Kasianov, Artem S; Kuzmin, Dmitry A; Putintseva, Yuliya A; Feranchuk, Sergey I; Shaposhnikov, Mikhail V; Fraifeld, Vadim E; Toren, Dmitri; Snezhkina, Anastasia V; Sitnik, Vasily V

2017-12-28

Gray whale, Eschrichtius robustus (E. robustus), is a single member of the family Eschrichtiidae, which is considered to be the most primitive in the class Cetacea. Gray whale is often described as a "living fossil". It is adapted to extreme marine conditions and has a high life expectancy (77 years). The assembly of a gray whale genome and transcriptome will allow to carry out further studies of whale evolution, longevity, and resistance to extreme environment. In this work, we report the first de novo assembly and primary analysis of the E. robustus genome and transcriptome based on kidney and liver samples. The presented draft genome assembly is complete by 55% in terms of a total genome length, but only by 24% in terms of the BUSCO complete gene groups, although 10,895 genes were identified. Transcriptome annotation and comparison with other whale species revealed robust expression of DNA repair and hypoxia-response genes, which is expected for whales. This preliminary study of the gray whale genome and transcriptome provides new data to better understand the whale evolution and the mechanisms of their adaptation to the hypoxic conditions.

A comprehensive comparison of RNA-Seq-based transcriptome analysis from reads to differential gene expression and cross-comparison with microarrays: a case study in Saccharomyces cerevisiae

PubMed Central

Nookaew, Intawat; Papini, Marta; Pornputtapong, Natapol; Scalcinati, Gionata; Fagerberg, Linn; Uhlén, Matthias; Nielsen, Jens

2012-01-01

RNA-seq, has recently become an attractive method of choice in the studies of transcriptomes, promising several advantages compared with microarrays. In this study, we sought to assess the contribution of the different analytical steps involved in the analysis of RNA-seq data generated with the Illumina platform, and to perform a cross-platform comparison based on the results obtained through Affymetrix microarray. As a case study for our work we, used the Saccharomyces cerevisiae strain CEN.PK 113-7D, grown under two different conditions (batch and chemostat). Here, we asses the influence of genetic variation on the estimation of gene expression level using three different aligners for read-mapping (Gsnap, Stampy and TopHat) on S288c genome, the capabilities of five different statistical methods to detect differential gene expression (baySeq, Cuffdiff, DESeq, edgeR and NOISeq) and we explored the consistency between RNA-seq analysis using reference genome and de novo assembly approach. High reproducibility among biological replicates (correlation ≥0.99) and high consistency between the two platforms for analysis of gene expression levels (correlation ≥0.91) are reported. The results from differential gene expression identification derived from the different statistical methods, as well as their integrated analysis results based on gene ontology annotation are in good agreement. Overall, our study provides a useful and comprehensive comparison between the two platforms (RNA-seq and microrrays) for gene expression analysis and addresses the contribution of the different steps involved in the analysis of RNA-seq data. PMID:22965124

Integrated metabolic flux and omics analysis of Synechocystis sp. PCC 6803 under mixotrophic and photoheterotrophic conditions.

PubMed

Nakajima, Tsubasa; Kajihata, Shuichi; Yoshikawa, Katsunori; Matsuda, Fumio; Furusawa, Chikara; Hirasawa, Takashi; Shimizu, Hiroshi

2014-09-01

Cyanobacteria have flexible metabolic capability that enables them to adapt to various environments. To investigate their underlying metabolic regulation mechanisms, we performed an integrated analysis of metabolic flux using transcriptomic and metabolomic data of a cyanobacterium Synechocystis sp. PCC 6803, under mixotrophic and photoheterotrophic conditions. The integrated analysis indicated drastic metabolic flux changes, with much smaller changes in gene expression levels and metabolite concentrations between the conditions, suggesting that the flux change was not caused mainly by the expression levels of the corresponding genes. Under photoheterotrophic conditions, created by the addition of the photosynthesis inhibitor atrazine in mixotrophic conditions, the result of metabolic flux analysis indicated the significant repression of carbon fixation and the activation of the oxidative pentose phosphate pathway (PPP). Moreover, we observed gluconeogenic activity of upstream of glycolysis, which enhanced the flux of the oxidative PPP to compensate for NADPH depletion due to the inhibition of the light reaction of photosynthesis. 'Omics' data suggested that these changes were probably caused by the repression of the gap1 gene, which functions as a control valve in the metabolic network. Since metabolic flux is the outcome of a complicated interplay of cellular components, integrating metabolic flux with other 'omics' layers can identify metabolic changes and narrow down these regulatory mechanisms more effectively. © The Author 2014. Published by Oxford University Press on behalf of Japanese Society of Plant Physiologists. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Transcriptome assembly, profiling and differential gene expression analysis of the halophyte Suaeda fruticosa provides insights into salt tolerance.

PubMed

Diray-Arce, Joann; Clement, Mark; Gul, Bilquees; Khan, M Ajmal; Nielsen, Brent L

2015-05-06

Improvement of crop production is needed to feed the growing world population as the amount and quality of agricultural land decreases and soil salinity increases. This has stimulated research on salt tolerance in plants. Most crops tolerate a limited amount of salt to survive and produce biomass, while halophytes (salt-tolerant plants) have the ability to grow with saline water utilizing specific biochemical mechanisms. However, little is known about the genes involved in salt tolerance. We have characterized the transcriptome of Suaeda fruticosa, a halophyte that has the ability to sequester salts in its leaves. Suaeda fruticosa is an annual shrub in the family Chenopodiaceae found in coastal and inland regions of Pakistan and Mediterranean shores. This plant is an obligate halophyte that grows optimally from 200-400 mM NaCl and can grow at up to 1000 mM NaCl. High throughput sequencing technology was performed to provide understanding of genes involved in the salt tolerance mechanism. De novo assembly of the transcriptome and analysis has allowed identification of differentially expressed and unique genes present in this non-conventional crop. Twelve sequencing libraries prepared from control (0 mM NaCl treated) and optimum (300 mM NaCl treated) plants were sequenced using Illumina Hiseq 2000 to investigate differential gene expression between shoots and roots of Suaeda fruticosa. The transcriptome was assembled de novo using Velvet and Oases k-45 and clustered using CDHIT-EST. There are 54,526 unigenes; among these 475 genes are downregulated and 44 are upregulated when samples from plants grown under optimal salt are compared with those grown without salt. BLAST analysis identified the differentially expressed genes, which were categorized in gene ontology terms and their pathways. This work has identified potential genes involved in salt tolerance in Suaeda fruticosa, and has provided an outline of tools to use for de novo transcriptome analysis. The assemblies that were used provide coverage of a considerable proportion of the transcriptome, which allows analysis of differential gene expression and identification of genes that may be involved in salt tolerance. The transcriptome may serve as a reference sequence for study of other succulent halophytes.

Increasing the source/sink ratio in Vitis vinifera (cv Sangiovese) induces extensive transcriptome reprogramming and modifies berry ripening

PubMed Central

2011-01-01

Background Cluster thinning is an agronomic practice in which a proportion of berry clusters are removed from the vine to increase the source/sink ratio and improve the quality of the remaining berries. Until now no transcriptomic data have been reported describing the mechanisms that underlie the agronomic and biochemical effects of thinning. Results We profiled the transcriptome of Vitis vinifera cv. Sangiovese berries before and after thinning at veraison using a genome-wide microarray representing all grapevine genes listed in the latest V1 gene prediction. Thinning increased the source/sink ratio from 0.6 to 1.2 m2 leaf area per kg of berries and boosted the sugar and anthocyanin content at harvest. Extensive transcriptome remodeling was observed in thinned vines 2 weeks after thinning and at ripening. This included the enhanced modulation of genes that are normally regulated during berry development and the induction of a large set of genes that are not usually expressed. Conclusion Cluster thinning has a profound effect on several important cellular processes and metabolic pathways including carbohydrate metabolism and the synthesis and transport of secondary products. The integrated agronomic, biochemical and transcriptomic data revealed that the positive impact of cluster thinning on final berry composition reflects a much more complex outcome than simply enhancing the normal ripening process. PMID:22192855

Transcriptomes Reveal Genetic Signatures Underlying Physiological Variations Imposed by Different Fermentation Conditions in Lactobacillus plantarum

PubMed Central

Bongers, Roger S.; van Bokhorst-van de Veen, Hermien; Wiersma, Anne; Overmars, Lex; Marco, Maria L.; Kleerebezem, Michiel

2012-01-01

Lactic acid bacteria (LAB) are utilized widely for the fermentation of foods. In the current post-genomic era, tools have been developed that explore genetic diversity among LAB strains aiming to link these variations to differential phenotypes observed in the strains investigated. However, these genotype-phenotype matching approaches fail to assess the role of conserved genes in the determination of physiological characteristics of cultures by environmental conditions. This manuscript describes a complementary approach in which Lactobacillus plantarum WCFS1 was fermented under a variety of conditions that differ in temperature, pH, as well as NaCl, amino acid, and O2 levels. Samples derived from these fermentations were analyzed by full-genome transcriptomics, paralleled by the assessment of physiological characteristics, e.g., maximum growth rate, yield, and organic acid profiles. A data-storage and -mining suite designated FermDB was constructed and exploited to identify correlations between fermentation conditions and industrially relevant physiological characteristics of L. plantarum, as well as the associated transcriptome signatures. Finally, integration of the specific fermentation variables with the transcriptomes enabled the reconstruction of the gene-regulatory networks involved. The fermentation-genomics platform presented here is a valuable complementary approach to earlier described genotype-phenotype matching strategies which allows the identification of transcriptome signatures underlying physiological variations imposed by different fermentation conditions. PMID:22802930

Analysis, annotation, and profiling of the oat seed transcriptome

USDA-ARS?s Scientific Manuscript database

Novel high-throughput next generation sequencing (NGS) technologies are providing opportunities to explore genomes and transcriptomes in a cost-effective manner. To construct a gene expression atlas of developing oat (Avena sativa) seeds, two software packages specifically designed for RNA-seq (Trin...

A comprehensive analysis of the human placenta transcriptome

USDA-ARS?s Scientific Manuscript database

As the conduit for nutrients and growth signals, the placenta is critical to establishing an environment sufficient for fetal growth and development. To better understand the mechanisms regulating placental development and gene expression, we characterized the transcriptome of term placenta from 20 ...

Genome-wide transcriptome and expression profile analysis of Phalaenopsis during explant browning.

PubMed

Xu, Chuanjun; Zeng, Biyu; Huang, Junmei; Huang, Wen; Liu, Yumei

2015-01-01

Explant browning presents a major problem for in vitro culture, and can lead to the death of the explant and failure of regeneration. Considerable work has examined the physiological mechanisms underlying Phalaenopsis leaf explant browning, but the molecular mechanisms of browning remain elusive. In this study, we used whole genome RNA sequencing to examine Phalaenopsis leaf explant browning at genome-wide level. We first used Illumina high-throughput technology to sequence the transcriptome of Phalaenopsis and then performed de novo transcriptome assembly. We assembled 79,434,350 clean reads into 31,708 isogenes and generated 26,565 annotated unigenes. We assigned Gene Ontology (GO) terms, Kyoto Encyclopedia of Genes and Genomes (KEGG) annotations, and potential Pfam domains to each transcript. Using the transcriptome data as a reference, we next analyzed the differential gene expression of explants cultured for 0, 3, and 6 d, respectively. We then identified differentially expressed genes (DEGs) before and after Phalaenopsis explant browning. We also performed GO, KEGG functional enrichment and Pfam analysis of all DEGs. Finally, we selected 11 genes for quantitative real-time PCR (qPCR) analysis to confirm the expression profile analysis. Here, we report the first comprehensive analysis of transcriptome and expression profiles during Phalaenopsis explant browning. Our results suggest that Phalaenopsis explant browning may be due in part to gene expression changes that affect the secondary metabolism, such as: phenylpropanoid pathway and flavonoid biosynthesis. Genes involved in photosynthesis and ATPase activity have been found to be changed at transcription level; these changes may perturb energy metabolism and thus lead to the decay of plant cells and tissues. This study provides comprehensive gene expression data for Phalaenopsis browning. Our data constitute an important resource for further functional studies to prevent explant browning.

Genome-Wide Transcriptome and Expression Profile Analysis of Phalaenopsis during Explant Browning

PubMed Central

Xu, Chuanjun; Zeng, Biyu; Huang, Junmei; Huang, Wen; Liu, Yumei

2015-01-01

Background Explant browning presents a major problem for in vitro culture, and can lead to the death of the explant and failure of regeneration. Considerable work has examined the physiological mechanisms underlying Phalaenopsis leaf explant browning, but the molecular mechanisms of browning remain elusive. In this study, we used whole genome RNA sequencing to examine Phalaenopsis leaf explant browning at genome-wide level. Methodology/Principal Findings We first used Illumina high-throughput technology to sequence the transcriptome of Phalaenopsis and then performed de novo transcriptome assembly. We assembled 79,434,350 clean reads into 31,708 isogenes and generated 26,565 annotated unigenes. We assigned Gene Ontology (GO) terms, Kyoto Encyclopedia of Genes and Genomes (KEGG) annotations, and potential Pfam domains to each transcript. Using the transcriptome data as a reference, we next analyzed the differential gene expression of explants cultured for 0, 3, and 6 d, respectively. We then identified differentially expressed genes (DEGs) before and after Phalaenopsis explant browning. We also performed GO, KEGG functional enrichment and Pfam analysis of all DEGs. Finally, we selected 11 genes for quantitative real-time PCR (qPCR) analysis to confirm the expression profile analysis. Conclusions/Significance Here, we report the first comprehensive analysis of transcriptome and expression profiles during Phalaenopsis explant browning. Our results suggest that Phalaenopsis explant browning may be due in part to gene expression changes that affect the secondary metabolism, such as: phenylpropanoid pathway and flavonoid biosynthesis. Genes involved in photosynthesis and ATPase activity have been found to be changed at transcription level; these changes may perturb energy metabolism and thus lead to the decay of plant cells and tissues. This study provides comprehensive gene expression data for Phalaenopsis browning. Our data constitute an important resource for further functional studies to prevent explant browning. PMID:25874455

EuPathDB: the eukaryotic pathogen genomics database resource

PubMed Central

Aurrecoechea, Cristina; Barreto, Ana; Basenko, Evelina Y.; Brestelli, John; Brunk, Brian P.; Cade, Shon; Crouch, Kathryn; Doherty, Ryan; Falke, Dave; Fischer, Steve; Gajria, Bindu; Harb, Omar S.; Heiges, Mark; Hertz-Fowler, Christiane; Hu, Sufen; Iodice, John; Kissinger, Jessica C.; Lawrence, Cris; Li, Wei; Pinney, Deborah F.; Pulman, Jane A.; Roos, David S.; Shanmugasundram, Achchuthan; Silva-Franco, Fatima; Steinbiss, Sascha; Stoeckert, Christian J.; Spruill, Drew; Wang, Haiming; Warrenfeltz, Susanne; Zheng, Jie

2017-01-01

The Eukaryotic Pathogen Genomics Database Resource (EuPathDB, http://eupathdb.org) is a collection of databases covering 170+ eukaryotic pathogens (protists & fungi), along with relevant free-living and non-pathogenic species, and select pathogen hosts. To facilitate the discovery of meaningful biological relationships, the databases couple preconfigured searches with visualization and analysis tools for comprehensive data mining via intuitive graphical interfaces and APIs. All data are analyzed with the same workflows, including creation of gene orthology profiles, so data are easily compared across data sets, data types and organisms. EuPathDB is updated with numerous new analysis tools, features, data sets and data types. New tools include GO, metabolic pathway and word enrichment analyses plus an online workspace for analysis of personal, non-public, large-scale data. Expanded data content is mostly genomic and functional genomic data while new data types include protein microarray, metabolic pathways, compounds, quantitative proteomics, copy number variation, and polysomal transcriptomics. New features include consistent categorization of searches, data sets and genome browser tracks; redesigned gene pages; effective integration of alternative transcripts; and a EuPathDB Galaxy instance for private analyses of a user's data. Forthcoming upgrades include user workspaces for private integration of data with existing EuPathDB data and improved integration and presentation of host–pathogen interactions. PMID:27903906

De novo transcriptomic analysis and development of EST-SSR markers in the Siberian tiger (Panthera tigris altaica).

PubMed

Lu, Taofeng; Sun, Yujiao; Ma, Qin; Zhu, Minghao; Liu, Dan; Ma, Jianzhang; Ma, Yuehui; Chen, Hongyan; Guan, Weijun

2016-12-01

The Siberian tiger, Panthera tigris altaica, is an endangered species, and much more work is needed to protect this species, which is still vulnerable to extinction. Conservation efforts may be supported by the genetic assessment of wild populations, for which highly specific microsatellite markers are required. However, only a limited amount of genetic sequence data is available for this species. To identify the genes involved in the lung transcriptome and to develop additional simple sequence repeat (SSR) markers for the Siberian tiger, we used high-throughput RNA-Seq to characterize the Siberian tiger transcriptome in lung tissue (designated 'PTA-lung') and a pooled tissue sample (designated 'PTA'). Approximately 47.5 % (33,187/69,836) of the lung transcriptome was annotated in four public databases (Nr, Swiss-Prot, KEGG, and COG). The annotated genes formed a potential pool for gene identification in the tiger. An analysis of the genes differentially expressed in the PTA lung, and PTA samples revealed that the tiger may have suffered a series of diseases before death. In total, 1062 non-redundant SSRs were identified in the Siberian tiger transcriptome. Forty-three primer pairs were randomly selected for amplification reactions, and 26 of the 43 pairs were also used to evaluate the levels of genetic polymorphism. Fourteen primer pairs (32.56 %) amplified products that were polymorphic in size in P. tigris altaica. In conclusion, the transcriptome sequences will provide a valuable genomic resource for genetic research, and these new SSR markers comprise a reasonable number of loci for the genetic analysis of wild and captive populations of P. tigris altaica.

Global transcriptome analysis of the C57BL/6J mouse testis by SAGE: evidence for nonrandom gene order.

PubMed

Divina, Petr; Vlcek, Cestmír; Strnad, Petr; Paces, Václav; Forejt, Jirí

2005-03-05

We generated the gene expression profile of the total testis from the adult C57BL/6J male mice using serial analysis of gene expression (SAGE). Two high-quality SAGE libraries containing a total of 76 854 tags were constructed. An extensive bioinformatic analysis and comparison of SAGE transcriptomes of the total testis, testicular somatic cells and other mouse tissues was performed and the theory of male-biased gene accumulation on the X chromosome was tested. We sorted out 829 genes predominantly expressed from the germinal part and 944 genes from the somatic part of the testis. The genes preferentially and specifically expressed in total testis and testicular somatic cells were identified by comparing the testis SAGE transcriptomes to the available transcriptomes of seven non-testis tissues. We uncovered chromosomal clusters of adjacent genes with preferential expression in total testis and testicular somatic cells by a genome-wide search and found that the clusters encompassed a significantly higher number of genes than expected by chance. We observed a significant 3.2-fold enrichment of the proportion of X-linked genes specific for testicular somatic cells, while the proportions of X-linked genes specific for total testis and for other tissues were comparable. In contrast to the tissue-specific genes, an under-representation of X-linked genes in the total testis transcriptome but not in the transcriptomes of testicular somatic cells and other tissues was detected. Our results provide new evidence in favor of the theory of male-biased genes accumulation on the X chromosome in testicular somatic cells and indicate the opposite action of the meiotic X-inactivation in testicular germ cells.

Global transcriptome analysis of the C57BL/6J mouse testis by SAGE: evidence for nonrandom gene order

PubMed Central

Divina, Petr; Vlček, Čestmír; Strnad, Petr; Pačes, Václav; Forejt, Jiří

2005-01-01

Background We generated the gene expression profile of the total testis from the adult C57BL/6J male mice using serial analysis of gene expression (SAGE). Two high-quality SAGE libraries containing a total of 76 854 tags were constructed. An extensive bioinformatic analysis and comparison of SAGE transcriptomes of the total testis, testicular somatic cells and other mouse tissues was performed and the theory of male-biased gene accumulation on the X chromosome was tested. Results We sorted out 829 genes predominantly expressed from the germinal part and 944 genes from the somatic part of the testis. The genes preferentially and specifically expressed in total testis and testicular somatic cells were identified by comparing the testis SAGE transcriptomes to the available transcriptomes of seven non-testis tissues. We uncovered chromosomal clusters of adjacent genes with preferential expression in total testis and testicular somatic cells by a genome-wide search and found that the clusters encompassed a significantly higher number of genes than expected by chance. We observed a significant 3.2-fold enrichment of the proportion of X-linked genes specific for testicular somatic cells, while the proportions of X-linked genes specific for total testis and for other tissues were comparable. In contrast to the tissue-specific genes, an under-representation of X-linked genes in the total testis transcriptome but not in the transcriptomes of testicular somatic cells and other tissues was detected. Conclusion Our results provide new evidence in favor of the theory of male-biased genes accumulation on the X chromosome in testicular somatic cells and indicate the opposite action of the meiotic X-inactivation in testicular germ cells. PMID:15748293

Determining the optimal number of independent components for reproducible transcriptomic data analysis.

PubMed

Kairov, Ulykbek; Cantini, Laura; Greco, Alessandro; Molkenov, Askhat; Czerwinska, Urszula; Barillot, Emmanuel; Zinovyev, Andrei

2017-09-11

Independent Component Analysis (ICA) is a method that models gene expression data as an action of a set of statistically independent hidden factors. The output of ICA depends on a fundamental parameter: the number of components (factors) to compute. The optimal choice of this parameter, related to determining the effective data dimension, remains an open question in the application of blind source separation techniques to transcriptomic data. Here we address the question of optimizing the number of statistically independent components in the analysis of transcriptomic data for reproducibility of the components in multiple runs of ICA (within the same or within varying effective dimensions) and in multiple independent datasets. To this end, we introduce ranking of independent components based on their stability in multiple ICA computation runs and define a distinguished number of components (Most Stable Transcriptome Dimension, MSTD) corresponding to the point of the qualitative change of the stability profile. Based on a large body of data, we demonstrate that a sufficient number of dimensions is required for biological interpretability of the ICA decomposition and that the most stable components with ranks below MSTD have more chances to be reproduced in independent studies compared to the less stable ones. At the same time, we show that a transcriptomics dataset can be reduced to a relatively high number of dimensions without losing the interpretability of ICA, even though higher dimensions give rise to components driven by small gene sets. We suggest a protocol of ICA application to transcriptomics data with a possibility of prioritizing components with respect to their reproducibility that strengthens the biological interpretation. Computing too few components (much less than MSTD) is not optimal for interpretability of the results. The components ranked within MSTD range have more chances to be reproduced in independent studies.

Integrated sequencing of exome and mRNA of large-sized single cells.

PubMed

Wang, Lily Yan; Guo, Jiajie; Cao, Wei; Zhang, Meng; He, Jiankui; Li, Zhoufang

2018-01-10

Current approaches of single cell DNA-RNA integrated sequencing are difficult to call SNPs, because a large amount of DNA and RNA is lost during DNA-RNA separation. Here, we performed simultaneous single-cell exome and transcriptome sequencing on individual mouse oocytes. Using microinjection, we kept the nuclei intact to avoid DNA loss, while retaining the cytoplasm inside the cell membrane, to maximize the amount of DNA and RNA captured from the single cell. We then conducted exome-sequencing on the isolated nuclei and mRNA-sequencing on the enucleated cytoplasm. For single oocytes, exome-seq can cover up to 92% of exome region with an average sequencing depth of 10+, while mRNA-sequencing reveals more than 10,000 expressed genes in enucleated cytoplasm, with similar performance for intact oocytes. This approach provides unprecedented opportunities to study DNA-RNA regulation, such as RNA editing at single nucleotide level in oocytes. In future, this method can also be applied to other large cells, including neurons, large dendritic cells and large tumour cells for integrated exome and transcriptome sequencing.

Transcriptome of interstitial cells of Cajal reveals unique and selective gene signatures

PubMed Central

Park, Paul J.; Fuchs, Robert; Wei, Lai; Jorgensen, Brian G.; Redelman, Doug; Ward, Sean M.; Sanders, Kenton M.

2017-01-01

Transcriptome-scale data can reveal essential clues into understanding the underlying molecular mechanisms behind specific cellular functions and biological processes. Transcriptomics is a continually growing field of research utilized in biomarker discovery. The transcriptomic profile of interstitial cells of Cajal (ICC), which serve as slow-wave electrical pacemakers for gastrointestinal (GI) smooth muscle, has yet to be uncovered. Using copGFP-labeled ICC mice and flow cytometry, we isolated ICC populations from the murine small intestine and colon and obtained their transcriptomes. In analyzing the transcriptome, we identified a unique set of ICC-restricted markers including transcription factors, epigenetic enzymes/regulators, growth factors, receptors, protein kinases/phosphatases, and ion channels/transporters. This analysis provides new and unique insights into the cellular and biological functions of ICC in GI physiology. Additionally, we constructed an interactive ICC genome browser (http://med.unr.edu/physio/transcriptome) based on the UCSC genome database. To our knowledge, this is the first online resource that provides a comprehensive library of all known genetic transcripts expressed in primary ICC. Our genome browser offers a new perspective into the alternative expression of genes in ICC and provides a valuable reference for future functional studies. PMID:28426719

Character trees from transcriptome data: Origin and individuation of morphological characters and the so-called "species signal".

PubMed

Musser, Jacob M; Wagner, Günter P

2015-11-01

We elaborate a framework for investigating the evolutionary history of morphological characters. We argue that morphological character trees generated by phylogenetic analysis of transcriptomes provide a useful tool for identifying causal gene expression differences underlying the development and evolution of morphological characters. They also enable rigorous testing of different models of morphological character evolution and origination, including the hypothesis that characters originate via divergence of repeated ancestral characters. Finally, morphological character trees provide evidence that character transcriptomes undergo concerted evolution. We argue that concerted evolution of transcriptomes can explain the so-called "species signal" found in several recent comparative transcriptome studies. The species signal is the phenomenon that transcriptomes cluster by species rather than character type, even though the characters are older than the respective species. We suggest the species signal is a natural consequence of concerted gene expression evolution resulting from mutations that alter gene regulatory network interactions shared by the characters under comparison. Thus, character trees generated from transcriptomes allow us to investigate the variational independence, or individuation, of morphological characters at the level of genetic programs. © 2015 Wiley Periodicals, Inc.

Analysis of insecticide resistance-related genes of the Carmine spider mite Tetranychus cinnabarinus based on a de novo assembled transcriptome.

PubMed

Xu, Zhifeng; Zhu, Wenyi; Liu, Yanchao; Liu, Xing; Chen, Qiushuang; Peng, Miao; Wang, Xiangzun; Shen, Guangmao; He, Lin

2014-01-01

The carmine spider mite (CSM), Tetranychus cinnabarinus, is an important pest mite in agriculture, because it can develop insecticide resistance easily. To gain valuable gene information and molecular basis for the future insecticide resistance study of CSM, the first transcriptome analysis of CSM was conducted. A total of 45,016 contigs and 25,519 unigenes were generated from the de novo transcriptome assembly, and 15,167 unigenes were annotated via BLAST querying against current databases, including nr, SwissProt, the Clusters of Orthologous Groups (COGs), Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO). Aligning the transcript to Tetranychus urticae genome, the 19255 (75.45%) of the transcripts had significant (e-value <10-5) matches to T. urticae DNA genome, 19111 sequences matched to T. urticae proteome with an average protein length coverage of 42.55%. Core Eukaryotic Genes Mapping Approach (CEGMA) analysis identified 435 core eukaryotic genes (CEGs) in the CSM dataset corresponding to 95% coverage. Ten gene categories that relate to insecticide resistance in arthropod were generated from CSM transcriptome, including 53 P450-, 22 GSTs-, 23 CarEs-, 1 AChE-, 7 GluCls-, 9 nAChRs-, 8 GABA receptor-, 1 sodium channel-, 6 ATPase- and 12 Cyt b genes. We developed significant molecular resources for T. cinnabarinus putatively involved in insecticide resistance. The transcriptome assembly analysis will significantly facilitate our study on the mechanism of adapting environmental stress (including insecticide) in CSM at the molecular level, and will be very important for developing new control strategies against this pest mite.

De Novo Transcriptome Assembly and Characterization of Lithospermum officinale to Discover Putative Genes Involved in Specialized Metabolites Biosynthesis.

PubMed

Rai, Amit; Nakaya, Taiki; Shimizu, Yohei; Rai, Megha; Nakamura, Michimi; Suzuki, Hideyuki; Saito, Kazuki; Yamazaki, Mami

2018-05-29

Lithospermum officinale is a valuable source of bioactive metabolites with medicinal and industrial values. However, little is known about genes involved in the biosynthesis of these metabolites, primarily due to the lack of genome or transcriptome resources. This study presents the first effort to establish and characterize de novo transcriptome assembly resource for L. officinale and expression analysis for three of its tissues, namely leaf, stem, and root. Using over 4Gbps of RNA-sequencing datasets, we obtained de novo transcriptome assembly of L. officinale , consisting of 77,047 unigenes with assembly N50 value as 1524 bps. Based on transcriptome annotation and functional classification, 52,766 unigenes were assigned with putative genes functions, gene ontology terms, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. KEGG pathway and gene ontology enrichment analysis using highly expressed unigenes across three tissues and targeted metabolome analysis showed active secondary metabolic processes enriched specifically in the root of L. officinale . Using co-expression analysis, we also identified 20 and 48 unigenes representing different enzymes of lithospermic/chlorogenic acid and shikonin biosynthesis pathways, respectively. We further identified 15 candidate unigenes annotated as cytochrome P450 with the highest expression in the root of L. officinale as novel genes with a role in key biochemical reactions toward shikonin biosynthesis. Thus, through this study, we not only generated a high-quality genomic resource for L. officinale but also propose candidate genes to be involved in shikonin biosynthesis pathways for further functional characterization. Georg Thieme Verlag KG Stuttgart · New York.

Perigone Lobe Transcriptome Analysis Provides Insights into Rafflesia cantleyi Flower Development.

PubMed

Lee, Xin-Wei; Mat-Isa, Mohd-Noor; Mohd-Elias, Nur-Atiqah; Aizat-Juhari, Mohd Afiq; Goh, Hoe-Han; Dear, Paul H; Chow, Keng-See; Haji Adam, Jumaat; Mohamed, Rahmah; Firdaus-Raih, Mohd; Wan, Kiew-Lian

2016-01-01

Rafflesia is a biologically enigmatic species that is very rare in occurrence and possesses an extraordinary morphology. This parasitic plant produces a gigantic flower up to one metre in diameter with no leaves, stem or roots. However, little is known about the floral biology of this species especially at the molecular level. In an effort to address this issue, we have generated and characterised the transcriptome of the Rafflesia cantleyi flower, and performed a comparison with the transcriptome of its floral bud to predict genes that are expressed and regulated during flower development. Approximately 40 million sequencing reads were generated and assembled de novo into 18,053 transcripts with an average length of 641 bp. Of these, more than 79% of the transcripts had significant matches to annotated sequences in the public protein database. A total of 11,756 and 7,891 transcripts were assigned to Gene Ontology categories and clusters of orthologous groups respectively. In addition, 6,019 transcripts could be mapped to 129 pathways in Kyoto Encyclopaedia of Genes and Genomes Pathway database. Digital abundance analysis identified 52 transcripts with very high expression in the flower transcriptome of R. cantleyi. Subsequently, analysis of differential expression between developing flower and the floral bud revealed a set of 105 transcripts with potential role in flower development. Our work presents a deep transcriptome resource analysis for the developing flower of R. cantleyi. Genes potentially involved in the growth and development of the R. cantleyi flower were identified and provide insights into biological processes that occur during flower development.

Integrated transcriptomic and proteomic analyses uncover regulatory roles of Nrf2 in the kidney

PubMed Central

Walsh, Joanne; Jenkins, Rosalind E.; Wong, Michael H. L.; Rowe, Cliff; Ricci, Emanuele; Ressel, Lorenzo; Fang, Yongxiang; Demougin, Philippe; Vukojevic, Vanja; O’Neill, Paul M.; Goldring, Christopher E.; Kitteringham, Neil R.; Park, B. Kevin; Odermatt, Alex; Copple, Ian M.

2015-01-01

The transcription factor Nrf2 exerts protective effects in numerous experimental models of acute kidney injury, and is a promising therapeutic target in chronic kidney disease. To provide a detailed insight into the regulatory roles of Nrf2 in the kidney, we performed integrated transcriptomic and proteomic analyses of kidney tissue from wild-type and Nrf2 knockout mice treated with the Nrf2 inducer methyl-2-cyano-3,12-dioxooleano-1,9-dien-28-oate (CDDO-Me, also known as bardoxolone methyl). After 24 hours, analyses identified 2561 transcripts and 240 proteins that were differentially expressed in the kidneys of Nrf2 knockout mice, compared to wild-type counterparts, and 3122 transcripts and 68 proteins that were differentially expressed in wild-type mice treated with CDDO-Me, compared to vehicle control. In light of their sensitivity to genetic and pharmacological modulation of renal Nrf2 activity, genes/proteins that regulate xenobiotic disposition, redox balance, the intra/extracellular transport of small molecules, and the supply of NADPH and other cellular fuels were found to be positively regulated by Nrf2 in the kidney. This was verified by qPCR, immunoblotting, pathway analysis and immunohistochemistry. In addition, the levels of NADPH and glutathione were found to be significantly decreased in the kidneys of Nrf2 knockout mice. Thus, Nrf2 regulates genes that coordinate homeostatic processes in the kidney, highlighting its potential as a novel therapeutic target. PMID:26422507

Identification and Characterization of Genes Involved in Benzylisoquinoline Alkaloid Biosynthesis in Coptis Species

PubMed Central

He, Si-Mei; Liang, Yan-Li; Cong, Kun; Chen, Geng; Zhao, Xiu; Zhao, Qi-Ming; Zhang, Jia-Jin; Wang, Xiao; Dong, Yang; Yang, Jian-Li; Zhang, Guang-Hui; Qian, Zhi-Long; Fan, Wei; Yang, Sheng-Chao

2018-01-01

The dried rhizomes of Coptis chinensis have been extensively used in heat clearing, dampness drying, fire draining, and detoxification by virtue of their major bioactive components, benzylisoquinoline alkaloids (BIAs). However, C. teeta and C. chinensis are occasionally interchanged, and current understanding of the molecular basis of BIA biosynthesis in these two species is limited. Here, berberine, coptisine, jatrorrhizine, and palmatine were detected in two species, and showed the highest contents in the roots, while epiberberine were found only in C. chinensis. Comprehensive transcriptome analysis of the roots and leaves of C. teeta and C. chinensis, respectively, identified 53 and 52 unigenes encoding enzymes potentially involved in BIA biosynthesis. By integrating probable biosynthetic pathways for BIAs, the jatrorrhizine biosynthesis ill-informed previously was further characterized. Two genes encoding norcoclaurine/norlaudanosoline 6-O-methyltransferases (Cc6OMT1 and Cc6OMT2) and one gene encoding norcoclaurine-7OMT (Ct7OMT) catalyzed enzymatically O-methylate (S)-norcoclaurine at C6 that yield (S)-coclaurine, along with a smaller amount of O-methylation occurred at C7, thereby forming its isomer (isococlaurine). In addition, scoulerine 9-OMT (CtSOMT) was determined to show strict substrate specificity, targeting (S)-scoulerine to yield (S)-tetrahydrocolumbamine. Taken together, the integration of the transcriptome and enzyme activity assays further provides new insight into molecular mechanisms underlying BIA biosynthesis in plants and identifies candidate genes for the study of synthetic biology in microorganisms. PMID:29915609

Editor's Highlight: Transgenic Zebrafish Reporter Lines as Alternative In Vivo Organ Toxicity Models.

PubMed

Poon, Kar Lai; Wang, Xingang; Lee, Serene G P; Ng, Ashley S; Goh, Wei Huang; Zhao, Zhonghua; Al-Haddawi, Muthafar; Wang, Haishan; Mathavan, Sinnakaruppan; Ingham, Philip W; McGinnis, Claudia; Carney, Tom J

2017-03-01

Organ toxicity, particularly liver toxicity, remains one of the major reasons for the termination of drug candidates in the development pipeline as well as withdrawal or restrictions of marketed drugs. A screening-amenable alternative in vivo model such as zebrafish would, therefore, find immediate application in the early prediction of unacceptable organ toxicity. To identify highly upregulated genes as biomarkers of toxic responses in the zebrafish model, a set of well-characterized reference drugs that cause drug-induced liver injury (DILI) in the clinic were applied to zebrafish larvae and adults. Transcriptome microarray analysis was performed on whole larvae or dissected adult livers. Integration of data sets from different drug treatments at different stages identified common upregulated detoxification pathways. Within these were candidate biomarkers which recurred in multiple treatments. We prioritized 4 highly upregulated genes encoding enzymes acting in distinct phases of the drug metabolism pathway. Through promoter isolation and fosmid recombineering, eGFP reporter transgenic zebrafish lines were generated and evaluated for their response to DILI drugs. Three of the 4 generated reporter lines showed a dose and time-dependent induction in endodermal organs to reference drugs and an expanded drug set. In conclusion, through integrated transcriptomics and transgenic approaches, we have developed parallel independent zebrafish in vivo screening platforms able to predict organ toxicities of preclinical drugs. © The Author 2017. Published by Oxford University Press on behalf of the Society of Toxicology. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Integrated transcriptome analysis of human iPS cells derived from a fragile X syndrome patient during neuronal differentiation.

PubMed

Lu, Ping; Chen, Xiaolong; Feng, Yun; Zeng, Qiao; Jiang, Cizhong; Zhu, Xianmin; Fan, Guoping; Xue, Zhigang

2016-11-01

Fragile X syndrome (FXS) patients carry the expansion of over 200 CGG repeats at the promoter of fragile X mental retardation 1 (FMR1), leading to decreased or absent expression of its encoded fragile X mental retardation protein (FMRP). However, the global transcriptional alteration by FMRP deficiency has not been well characterized at single nucleotide resolution, i.e., RNA-seq. Here, we performed in-vitro neuronal differentiation of human induced pluripotent stem (iPS) cells that were derived from fibroblasts of a FXS patient (FXS-iPSC). We then performed RNA-seq and examined the transcriptional misregulation at each intermediate stage during in-vitro differentiation of FXS-iPSC into neurons. After thoroughly analyzing the transcriptomic data and integrating them with those from other platforms, we found up-regulation of many genes encoding TFs for neuronal differentiation (WNT1, BMP4, POU3F4, TFAP2C, and PAX3), down-regulation of potassium channels (KCNA1, KCNC3, KCNG2, KCNIP4, KCNJ3, KCNK9, and KCNT1) and altered temporal regulation of SHANK1 and NNAT in FXS-iPSC derived neurons, indicating impaired neuronal differentiation and function in FXS patients. In conclusion, we demonstrated that the FMRP deficiency in FXS patients has significant impact on the gene expression patterns during development, which will help to discover potential targeting candidates for the cure of FXS symptoms.

Spectroscopic and Statistical Techniques for Information Recovery in Metabonomics and Metabolomics

NASA Astrophysics Data System (ADS)

Lindon, John C.; Nicholson, Jeremy K.

2008-07-01

Methods for generating and interpreting metabolic profiles based on nuclear magnetic resonance (NMR) spectroscopy, mass spectrometry (MS), and chemometric analysis methods are summarized and the relative strengths and weaknesses of NMR and chromatography-coupled MS approaches are discussed. Given that all data sets measured to date only probe subsets of complex metabolic profiles, we describe recent developments for enhanced information recovery from the resulting complex data sets, including integration of NMR- and MS-based metabonomic results and combination of metabonomic data with data from proteomics, transcriptomics, and genomics. We summarize the breadth of applications, highlight some current activities, discuss the issues relating to metabonomics, and identify future trends.

Spectroscopic and statistical techniques for information recovery in metabonomics and metabolomics.

PubMed

Lindon, John C; Nicholson, Jeremy K

2008-01-01

Methods for generating and interpreting metabolic profiles based on nuclear magnetic resonance (NMR) spectroscopy, mass spectrometry (MS), and chemometric analysis methods are summarized and the relative strengths and weaknesses of NMR and chromatography-coupled MS approaches are discussed. Given that all data sets measured to date only probe subsets of complex metabolic profiles, we describe recent developments for enhanced information recovery from the resulting complex data sets, including integration of NMR- and MS-based metabonomic results and combination of metabonomic data with data from proteomics, transcriptomics, and genomics. We summarize the breadth of applications, highlight some current activities, discuss the issues relating to metabonomics, and identify future trends.

Epigenomics of autoimmune diseases.

PubMed

Gupta, Bhawna; Hawkins, R David

2015-03-01

Autoimmune diseases are complex disorders of largely unknown etiology. Genetic studies have identified a limited number of causal genes from a marginal number of individuals, and demonstrated a high degree of discordance in monozygotic twins. Studies have begun to reveal epigenetic contributions to these diseases, primarily through the study of DNA methylation, but chromatin and non-coding RNA changes are also emerging. Moving forward an integrative analysis of genomic, transcriptomic and epigenomic data, with the latter two coming from specific cell types, will provide an understanding that has been missed from genetics alone. We provide an overview of the current state of the field and vision for deriving the epigenomics of autoimmunity.

The De Novo Transcriptome and Its Functional Annotation in the Seed Beetle Callosobruchus maculatus.

PubMed

Sayadi, Ahmed; Immonen, Elina; Bayram, Helen; Arnqvist, Göran

2016-01-01

Despite their unparalleled biodiversity, the genomic resources available for beetles (Coleoptera) remain relatively scarce. We present an integrative and high quality annotated transcriptome of the beetle Callosobruchus maculatus, an important and cosmopolitan agricultural pest as well as an emerging model species in ecology and evolutionary biology. Using Illumina sequencing technology, we sequenced 492 million read pairs generated from 51 samples of different developmental stages (larvae, pupae and adults) of C. maculatus. Reads were de novo assembled using the Trinity software, into a single combined assembly as well as into three separate assemblies based on data from the different developmental stages. The combined assembly generated 218,192 transcripts and 145,883 putative genes. Putative genes were annotated with the Blast2GO software and the Trinotate pipeline. In total, 33,216 putative genes were successfully annotated using Blastx against the Nr (non-redundant) database and 13,382 were assigned to 34,100 Gene Ontology (GO) terms. We classified 5,475 putative genes into Clusters of Orthologous Groups (COG) and 116 metabolic pathways maps were predicted based on the annotation. Our analyses suggested that the transcriptional specificity increases with ontogeny. For example, out of 33,216 annotated putative genes, 51 were only expressed in larvae, 63 only in pupae and 171 only in adults. Our study illustrates the importance of including samples from several developmental stages when the aim is to provide an integrative and high quality annotated transcriptome. Our results will represent an invaluable resource for those working with the ecology, evolution and pest control of C. maculatus, as well for comparative studies of the transcriptomics and genomics of beetles more generally.

The De Novo Transcriptome and Its Functional Annotation in the Seed Beetle Callosobruchus maculatus

PubMed Central

Sayadi, Ahmed; Immonen, Elina; Bayram, Helen

2016-01-01

Despite their unparalleled biodiversity, the genomic resources available for beetles (Coleoptera) remain relatively scarce. We present an integrative and high quality annotated transcriptome of the beetle Callosobruchus maculatus, an important and cosmopolitan agricultural pest as well as an emerging model species in ecology and evolutionary biology. Using Illumina sequencing technology, we sequenced 492 million read pairs generated from 51 samples of different developmental stages (larvae, pupae and adults) of C. maculatus. Reads were de novo assembled using the Trinity software, into a single combined assembly as well as into three separate assemblies based on data from the different developmental stages. The combined assembly generated 218,192 transcripts and 145,883 putative genes. Putative genes were annotated with the Blast2GO software and the Trinotate pipeline. In total, 33,216 putative genes were successfully annotated using Blastx against the Nr (non-redundant) database and 13,382 were assigned to 34,100 Gene Ontology (GO) terms. We classified 5,475 putative genes into Clusters of Orthologous Groups (COG) and 116 metabolic pathways maps were predicted based on the annotation. Our analyses suggested that the transcriptional specificity increases with ontogeny. For example, out of 33,216 annotated putative genes, 51 were only expressed in larvae, 63 only in pupae and 171 only in adults. Our study illustrates the importance of including samples from several developmental stages when the aim is to provide an integrative and high quality annotated transcriptome. Our results will represent an invaluable resource for those working with the ecology, evolution and pest control of C. maculatus, as well for comparative studies of the transcriptomics and genomics of beetles more generally. PMID:27442123

Transcriptome profiling reveals regulatory mechanisms underlying Corolla Senescence in Petunia

USDA-ARS?s Scientific Manuscript database

Genetic regulatory mechanisms that govern petal natural senescence in petunia is complicated and unclear. To identify key genes and pathways that regulate the process, we initiated a transcriptome analysis in petunia petals at four developmental time points, including petal opening without anthesis ...

Placental transcriptome co-expression analysis reveals conserved regulatory program across gestation

USDA-ARS?s Scientific Manuscript database

Mammalian development in utero is absolutely dependent on proper placental development, which is ultimately regulated by the placental genome. The regulation of the placental genome can be directly studied by exploring the underlying organization of the placental transcriptome through a systematic a...

De novo Assembly of the Burying Beetle Nicrophorus orbicollis (Coleoptera: Silphidae) Transcriptome Across Developmental Stages with Identification of Key Immune Transcripts

PubMed Central

Won, Harim I.; Schulze, Thomas T.; Clement, Emalie J.; Watson, Gabrielle F.; Watson, Sean M.; Warner, Rosalie C.; Ramler, Elizabeth A. M.; Witte, Elias J.; Schoenbeck, Mark A.; Rauter, Claudia M.; Davis, Paul H.

2018-01-01

Burying beetles (Nicrophorus spp.) are among the relatively few insects that provide parental care while not belonging to the eusocial insects such as ants or bees. This behavior incurs energy costs as evidenced by immune deficits and shorter life-spans in reproducing beetles. In the absence of an assembled transcriptome, relatively little is known concerning the molecular biology of these beetles. This work details the assembly and analysis of the Nicrophorus orbicollis transcriptome at multiple developmental stages. RNA-Seq reads were obtained by next-generation sequencing and the transcriptome was assembled using the Trinity assembler. Validation of the assembly was performed by functional characterization using Gene Ontology (GO), Eukaryotic Orthologous Groups (KOG), and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. Differential expression analysis highlights developmental stage-specific expression patterns, and immunity-related transcripts are discussed. The data presented provides a valuable molecular resource to aid further investigation into immunocompetence throughout this organism's sexual development. PMID:29707046

Systems analysis of transcriptome data provides new hypotheses about Arabidopsis root response to nitrate treatments

PubMed Central

Canales, Javier; Moyano, Tomás C.; Villarroel, Eva; Gutiérrez, Rodrigo A.

2014-01-01

Nitrogen (N) is an essential macronutrient for plant growth and development. Plants adapt to changes in N availability partly by changes in global gene expression. We integrated publicly available root microarray data under contrasting nitrate conditions to identify new genes and functions important for adaptive nitrate responses in Arabidopsis thaliana roots. Overall, more than 2000 genes exhibited changes in expression in response to nitrate treatments in Arabidopsis thaliana root organs. Global regulation of gene expression by nitrate depends largely on the experimental context. However, despite significant differences from experiment to experiment in the identity of regulated genes, there is a robust nitrate response of specific biological functions. Integrative gene network analysis uncovered relationships between nitrate-responsive genes and 11 highly co-expressed gene clusters (modules). Four of these gene network modules have robust nitrate responsive functions such as transport, signaling, and metabolism. Network analysis hypothesized G2-like transcription factors are key regulatory factors controlling transport and signaling functions. Our meta-analysis highlights the role of biological processes not studied before in the context of the nitrate response such as root hair development and provides testable hypothesis to advance our understanding of nitrate responses in plants. PMID:24570678

Snail1 transcription factor controls telomere transcription and integrity

PubMed Central

Mazzolini, Rocco; Gonzàlez, Núria; Garcia-Garijo, Andrea; Millanes-Romero, Alba; Peiró, Sandra; Smith, Susan

2018-01-01

Abstract Besides controlling epithelial-to-mesenchymal transition (EMT) and cell invasion, the Snail1 transcriptional factor also provides cells with cancer stem cell features. Since telomere maintenance is essential for stemness, we have examined the control of telomere integrity by Snail1. Fluorescence in situ hybridization (FISH) analysis indicates that Snail1-depleted mouse mesenchymal stem cells (MSC) have both a dramatic increase of telomere alterations and shorter telomeres. Remarkably, Snail1-deficient MSC present higher levels of both telomerase activity and the long non-coding RNA called telomeric repeat-containing RNA (TERRA), an RNA that controls telomere integrity. Accordingly, Snail1 expression downregulates expression of the telomerase gene (TERT) as well as of TERRA 2q, 11q and 18q. TERRA and TERT are transiently downregulated during TGFβ-induced EMT in NMuMG cells, correlating with Snail1 expression. Global transcriptome analysis indicates that ectopic expression of TERRA affects the transcription of some genes induced during EMT, such as fibronectin, whereas that of TERT does not modify those genes. We propose that Snail1 repression of TERRA is required not only for telomere maintenance but also for the expression of a subset of mesenchymal genes. PMID:29059385

In vitro downregulated hypoxia transcriptome is associated with poor prognosis in breast cancer.

PubMed

Abu-Jamous, Basel; Buffa, Francesca M; Harris, Adrian L; Nandi, Asoke K

2017-06-15

Hypoxia is a characteristic of breast tumours indicating poor prognosis. Based on the assumption that those genes which are up-regulated under hypoxia in cell-lines are expected to be predictors of poor prognosis in clinical data, many signatures of poor prognosis were identified. However, it was observed that cell line data do not always concur with clinical data, and therefore conclusions from cell line analysis should be considered with caution. As many transcriptomic cell-line datasets from hypoxia related contexts are available, integrative approaches which investigate these datasets collectively, while not ignoring clinical data, are required. We analyse sixteen heterogeneous breast cancer cell-line transcriptomic datasets in hypoxia-related conditions collectively by employing the unique capabilities of the method, UNCLES, which integrates clustering results from multiple datasets and can address questions that cannot be answered by existing methods. This has been demonstrated by comparison with the state-of-the-art iCluster method. From this collection of genome-wide datasets include 15,588 genes, UNCLES identified a relatively high number of genes (>1000 overall) which are consistently co-regulated over all of the datasets, and some of which are still poorly understood and represent new potential HIF targets, such as RSBN1 and KIAA0195. Two main, anti-correlated, clusters were identified; the first is enriched with MYC targets participating in growth and proliferation, while the other is enriched with HIF targets directly participating in the hypoxia response. Surprisingly, in six clinical datasets, some sub-clusters of growth genes are found consistently positively correlated with hypoxia response genes, unlike the observation in cell lines. Moreover, the ability to predict bad prognosis by a combined signature of one sub-cluster of growth genes and one sub-cluster of hypoxia-induced genes appears to be comparable and perhaps greater than that of known hypoxia signatures. We present a clustering approach suitable to integrate data from diverse experimental set-ups. Its application to breast cancer cell line datasets reveals new hypoxia-regulated signatures of genes which behave differently when in vitro (cell-line) data is compared with in vivo (clinical) data, and are of a prognostic value comparable or exceeding the state-of-the-art hypoxia signatures.

Transcriptional profiling of CD31(+) cells isolated from murine embryonic stem cells.

PubMed

Mariappan, Devi; Winkler, Johannes; Chen, Shuhua; Schulz, Herbert; Hescheler, Jürgen; Sachinidis, Agapios

2009-02-01

Identification of genes involved in endothelial differentiation is of great interest for the understanding of the cellular and molecular mechanisms involved in the development of new blood vessels. Mouse embryonic stem (mES) cells serve as a potential source of endothelial cells for transcriptomic analysis. We isolated endothelial cells from 8-days old embryoid bodies by immuno-magnetic separation using platelet endothelial cell adhesion molecule-1 (also known as CD31) expressed on both early and mature endothelial cells. CD31(+) cells exhibit endothelial-like behavior by being able to incorporate DiI-labeled acetylated low-density lipoprotein as well as form tubular structures on matrigel. Quantitative and semi-quantitative PCR analysis further demonstrated the increased expression of endothelial transcripts. To ascertain the specific transcriptomic identity of the CD31(+) cells, large-scale microarray analysis was carried out. Comparative bioinformatic analysis reveals an enrichment of the gene ontology categories angiogenesis, blood vessel morphogenesis, vasculogenesis and blood coagulation in the CD31(+) cell population. Based on the transcriptomic signatures of the CD31(+) cells, we conclude that this ES cell-derived population contains endothelial-like cells expressing a mesodermal marker BMP2 and possess an angiogenic potential. The transcriptomic characterization of CD31(+) cells enables an in vitro functional genomic model to identify genes required for angiogenesis.

RCAS: an RNA centric annotation system for transcriptome-wide regions of interest.

PubMed

Uyar, Bora; Yusuf, Dilmurat; Wurmus, Ricardo; Rajewsky, Nikolaus; Ohler, Uwe; Akalin, Altuna

2017-06-02

In the field of RNA, the technologies for studying the transcriptome have created a tremendous potential for deciphering the puzzles of the RNA biology. Along with the excitement, the unprecedented volume of RNA related omics data is creating great challenges in bioinformatics analyses. Here, we present the RNA Centric Annotation System (RCAS), an R package, which is designed to ease the process of creating gene-centric annotations and analysis for the genomic regions of interest obtained from various RNA-based omics technologies. The design of RCAS is modular, which enables flexible usage and convenient integration with other bioinformatics workflows. RCAS is an R/Bioconductor package but we also created graphical user interfaces including a Galaxy wrapper and a stand-alone web service. The application of RCAS on published datasets shows that RCAS is not only able to reproduce published findings but also helps generate novel knowledge and hypotheses. The meta-gene profiles, gene-centric annotation, motif analysis and gene-set analysis provided by RCAS provide contextual knowledge which is necessary for understanding the functional aspects of different biological events that involve RNAs. In addition, the array of different interfaces and deployment options adds the convenience of use for different levels of users. RCAS is available at http://bioconductor.org/packages/release/bioc/html/RCAS.html and http://rcas.mdc-berlin.de. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Spatial analysis of lipid metabolites and expressed genes reveals tissue-specific heterogeneity of lipid metabolism in high- and low-oil Brassica napus L. seeds.

PubMed

Lu, Shaoping; Sturtevant, Drew; Aziz, Mina; Jin, Cheng; Li, Qing; Chapman, Kent D; Guo, Liang

2018-06-01

Despite the importance of oilseeds to worldwide human nutrition, and more recently to the production of bio-based diesel fuels, the detailed mechanisms regulating seed oil biosynthesis remain only partly understood, especially from a tissue-specific perspective. Here, we investigated the spatial distributions of lipid metabolites and transcripts involved in oil biosynthesis from seeds of two low-erucic acid genotypes of Brassica napus with high and low seed-oil content. Integrated results from matrix-assisted laser desorption/ionization-mass spectrometry imaging (MALDI-MSI) of lipids in situ, lipidome profiling of extracts from seed tissues, and tissue-specific transcriptome analysis revealed complex spatial distribution patterns of lipids and transcripts. In general, it appeared that many triacylglycerol and phosphatidylcholine species distributed heterogeneously throughout the embryos. Tissue-specific transcriptome analysis identified key genes involved in de novo fatty acid biosynthesis in plastid, triacylglycerols assembly and lipid droplet packaging in the endoplasmic reticulum (ER) that may contribute to the high or low oil phenotype and heterogeneity of lipid distribution. Our results imply that transcriptional regulation represents an important means of impacting lipid compartmentalization in oil seeds. While much information remains to be learned about the intricacies of seed oil accumulation and distribution, these studies highlight the advances that come from evaluating lipid metabolism within a spatial context and with multiple omics level datasets. © 2018 The Authors The Plant Journal © 2018 John Wiley & Sons Ltd.

Integration of Next Generation Sequencing and EPR Analysis to Uncover Molecular Mechanism Underlying Shell Color Variation in Scallops

PubMed Central

Sun, Xiujun; Liu, Zhihong; Zhou, Liqing; Wu, Biao; Dong, Yinghui; Yang, Aiguo

2016-01-01

The Yesso scallop Patinopecten yessoensis displays polymorphism in shell colors, which is of great interest for the scallop industry. To identify genes involved in the shell coloration, in the present study, we investigate the transcriptome differences by Illumina digital gene expression (DGE) analysis in two extreme color phenotypes, Red and White. Illumina sequencing yields a total of 62,715,364 clean sequence reads, and more than 85% reads are mapped into our previously sequenced transcriptome. There are 25 significantly differentially expressed genes between Red and White scallops. EPR (Electron paramagnetic resonance) analysis has identified EPR spectra of pheomelanin and eumelanin in the red shells, but not in the white shells. Compared to the Red scallops, the White scallops have relatively higher mRNA expression in tyrosinase genes, but lower expression in other melanogensis-associated genes. Meantime, the relatively lower tyrosinase protein and decreased tyrosinase activity in White scallops are suggested to be associated with the lack of melanin in the white shells. Our findings highlight the functional roles of melanogensis-associated genes in the melanization process of scallop shells, and shed new lights on the transcriptional and post-transcriptional mechanisms in the regulation of tyrosinase activity during the process of melanin synthesis. The present results will assist our molecular understanding of melanin synthesis underlying shell color polymorphism in scallops, as well as other bivalves, and also help the color-based breeding in shellfish aquaculture. PMID:27563719

pico-PLAZA, a genome database of microbial photosynthetic eukaryotes.

PubMed

Vandepoele, Klaas; Van Bel, Michiel; Richard, Guilhem; Van Landeghem, Sofie; Verhelst, Bram; Moreau, Hervé; Van de Peer, Yves; Grimsley, Nigel; Piganeau, Gwenael

2013-08-01

With the advent of next generation genome sequencing, the number of sequenced algal genomes and transcriptomes is rapidly growing. Although a few genome portals exist to browse individual genome sequences, exploring complete genome information from multiple species for the analysis of user-defined sequences or gene lists remains a major challenge. pico-PLAZA is a web-based resource (http://bioinformatics.psb.ugent.be/pico-plaza/) for algal genomics that combines different data types with intuitive tools to explore genomic diversity, perform integrative evolutionary sequence analysis and study gene functions. Apart from homologous gene families, multiple sequence alignments, phylogenetic trees, Gene Ontology, InterPro and text-mining functional annotations, different interactive viewers are available to study genome organization using gene collinearity and synteny information. Different search functions, documentation pages, export functions and an extensive glossary are available to guide non-expert scientists. To illustrate the versatility of the platform, different case studies are presented demonstrating how pico-PLAZA can be used to functionally characterize large-scale EST/RNA-Seq data sets and to perform environmental genomics. Functional enrichments analysis of 16 Phaeodactylum tricornutum transcriptome libraries offers a molecular view on diatom adaptation to different environments of ecological relevance. Furthermore, we show how complementary genomic data sources can easily be combined to identify marker genes to study the diversity and distribution of algal species, for example in metagenomes, or to quantify intraspecific diversity from environmental strains. © 2013 John Wiley & Sons Ltd and Society for Applied Microbiology.

Comparative transcriptome analysis to investigate the potential role of miRNAs in milk protein/fat quality.

PubMed

Wang, Xuehui; Zhang, Li; Jin, Jing; Xia, Anting; Wang, Chunmei; Cui, Yingjun; Qu, Bo; Li, Qingzhang; Sheng, Chunyan

2018-04-19

miRNAs play an important role in the processes of cell differentiation, biological development, and physiology. Here we investigated the molecular mechanisms regulating milk secretion and quality in dairy cows via transcriptome analyses of mammary gland tissues from dairy cows during the high-protein/high-fat, low-protein/low-fat or dry periods. To characterize the important roles of miRNAs and mRNAs in milk quality and to elucidate their regulatory networks in relation to milk secretion and quality, an integrated analysis was performed. A total of 25 core miRNAs were found to be differentially expressed (DE) during lactation compared to non-lactation, and these miRNAs were involved in epithelial cell terminal differentiation and mammary gland development. In addition, comprehensive analysis of mRNA and miRNA expression between high-protein/high-fat group and low-protein/low-fat groups indicated that, 38 miRNAs and 944 mRNAs were differentially expressed between them. Furthermore, 38 DE miRNAs putatively negatively regulated 253 DE mRNAs. The putative genes (253 DE mRNAs) were enriched in lipid biosynthetic process and amino acid transmembrane transporter activity. Moreover, putative DE genes were significantly enriched in fatty acid (FA) metabolism, biosynthesis of amino acids, synthesis and degradation of ketone bodies and biosynthesis of unsaturated FAs. Our results suggest that DE miRNAs might play roles as regulators of milk quality and milk secretion during mammary gland differentiation.

Complementary transcriptome and proteome profiling in cabbage buds of a recessive male sterile mutant provides new insights into male reproductive development.

PubMed

Ji, Jialei; Yang, Limei; Fang, Zhiyuan; Zhuang, Mu; Zhang, Yangyong; Lv, Honghao; Liu, Yumei; Li, Zhansheng

2018-05-15

Plant male reproductive development is a very complex biological process that involves multiple metabolic pathways. To reveal novel insights into male reproductive development, we conducted an integrated profiling of gene activity in the developing buds of a cabbage recessive genetic male sterile mutant. Using RNA-Seq and label-free quantitative proteomics, 2881 transcripts and 1245 protein species were identified with significant differential abundance between the male sterile line 83121A and its isogenic maintainer line 83121B. Analyses of function annotations and correlations between transcriptome and proteome and protein interaction networks were also conducted, which suggested that the male sterility involves a complex regulatory pattern. Moreover, several key biological processes, such as fatty acid metabolism, tapetosome biosynthesis, amino acid metabolism and protein synthesis and degradation were identified as being of relevance to male reproductive development. A large number of protein species involved in sporopollenin synthesis, amino acid synthesis, ribosome assembly, protein processing in endoplasmic reticulum and lipid transfer were observed to be significantly down-accumulated in 83121A buds, indicating their potential roles in the regulation of cabbage microspore abortion. In summary, the conjoint analysis of the transcriptome and proteome provided a global picture regarding the molecular dynamics in male sterile buds of 83121A. Male sterile mutants are excellent materials for the study of plant male reproductive development. This study revealed the molecular dynamics of recessive male sterility in cabbage at the transcriptome and proteome levels, which deepens our understanding of the metabolic pathways involved in male development. Moreover, the male sterility-related genes identified in this study could provide a reference for the artificial regulation of cabbage fertility by using genetic engineering technology, which may result in potential applications in agriculture such as production of hybrid seeds using male sterility. Copyright © 2018 Elsevier B.V. All rights reserved.

Benchmark Dose Modeling Estimates of the Concentrations of Inorganic Arsenic That Induce Changes to the Neonatal Transcriptome, Proteome, and Epigenome in a Pregnancy Cohort.

PubMed

Rager, Julia E; Auerbach, Scott S; Chappell, Grace A; Martin, Elizabeth; Thompson, Chad M; Fry, Rebecca C

2017-10-16

Prenatal inorganic arsenic (iAs) exposure influences the expression of critical genes and proteins associated with adverse outcomes in newborns, in part through epigenetic mediators. The doses at which these genomic and epigenomic changes occur have yet to be evaluated in the context of dose-response modeling. The goal of the present study was to estimate iAs doses that correspond to changes in transcriptomic, proteomic, epigenomic, and integrated multi-omic signatures in human cord blood through benchmark dose (BMD) modeling. Genome-wide DNA methylation, microRNA expression, mRNA expression, and protein expression levels in cord blood were modeled against total urinary arsenic (U-tAs) levels from pregnant women exposed to varying levels of iAs. Dose-response relationships were modeled in BMDExpress, and BMDs representing 10% response levels were estimated. Overall, DNA methylation changes were estimated to occur at lower exposure concentrations in comparison to other molecular endpoints. Multi-omic module eigengenes were derived through weighted gene co-expression network analysis, representing co-modulated signatures across transcriptomic, proteomic, and epigenomic profiles. One module eigengene was associated with decreased gestational age occurring alongside increased iAs exposure. Genes/proteins within this module eigengene showed enrichment for organismal development, including potassium voltage-gated channel subfamily Q member 1 (KCNQ1), an imprinted gene showing differential methylation and expression in response to iAs. Modeling of this prioritized multi-omic module eigengene resulted in a BMD(BMDL) of 58(45) μg/L U-tAs, which was estimated to correspond to drinking water arsenic concentrations of 51(40) μg/L. Results are in line with epidemiological evidence supporting effects of prenatal iAs occurring at levels <100 μg As/L urine. Together, findings present a variety of BMD measures to estimate doses at which prenatal iAs exposure influences neonatal outcome-relevant transcriptomic, proteomic, and epigenomic profiles.

De novo transcriptome assembly and RNA-Seq expression analysis in blood from beluga whales of Bristol Bay, AK.

PubMed

Morey, Jeanine S; Burek Huntington, Kathy A; Campbell, Michelle; Clauss, Tonya M; Goertz, Caroline E; Hobbs, Roderick C; Lunardi, Denise; Moors, Amanda J; Neely, Marion G; Schwacke, Lori H; Van Dolah, Frances M

2017-10-01

Assessing the health of marine mammal sentinel species is crucial to understanding the impacts of environmental perturbations on marine ecosystems and human health. In Arctic regions, beluga whales, Delphinapterus leucas, are upper level predators that may serve as a sentinel species, potentially forecasting impacts on human health. While gene expression profiling from blood transcriptomes has widely been used to assess health status and environmental exposures in human and veterinary medicine, its use in wildlife has been limited due to the lack of available genomes and baseline data. To this end we constructed the first beluga whale blood transcriptome de novo from samples collected during annual health assessments of the healthy Bristol Bay, AK stock during 2012-2014 to establish baseline information on the content and variation of the beluga whale blood transcriptome. The Trinity transcriptome assembly from beluga was comprised of 91,325 transcripts that represented a wide array of cellular functions and processes and was extremely similar in content to the blood transcriptome of another cetacean, the bottlenose dolphin. Expression of hemoglobin transcripts was much lower in beluga (25.6% of TPM, transcripts per million) than has been observed in many other mammals. A T12A amino acid substitution in the HBB sequence of beluga whales, but not bottlenose dolphins, was identified and may play a role in low temperature adaptation. The beluga blood transcriptome was extremely stable between sex and year, with no apparent clustering of samples by principle components analysis and <4% of genes differentially expressed (EBseq, FDR<0.05). While the impacts of season, sexual maturity, disease, and geography on the beluga blood transcriptome must be established, the presence of transcripts involved in stress, detoxification, and immune functions indicate that blood gene expression analyses may provide information on health status and exposure. This study provides a wealth of transcriptomic data on beluga whales and provides a sizeable pool of preliminary data for comparison with other studies in beluga whale. Copyright © 2017 Elsevier B.V. All rights reserved.

De novo transcriptome of Ischnura elegans provides insights into sensory biology, colour and vision genes.

PubMed

Chauhan, Pallavi; Hansson, Bengt; Kraaijeveld, Ken; de Knijff, Peter; Svensson, Erik I; Wellenreuther, Maren

2014-09-22

There is growing interest in odonates (damselflies and dragonflies) as model organisms in ecology and evolutionary biology but the development of genomic resources has been slow. So far only one draft genome (Ladona fulva) and one transcriptome assembly (Enallagma hageni) have been published. Odonates have some of the most advanced visual systems among insects and several species are colour polymorphic, and genomic and transcriptomic data would allow studying the genomic architecture of these interesting traits and make detailed comparative studies between related species possible. Here, we present a comprehensive de novo transcriptome assembly for the blue-tailed damselfly Ischnura elegans (Odonata: Coenagrionidae) built from short-read RNA-seq data. The transcriptome analysis in this paper provides a first step towards identifying genes and pathways underlying the visual and colour systems in this insect group. Illumina RNA sequencing performed on tissues from the head, thorax and abdomen generated 428,744,100 paired-ends reads amounting to 110 Gb of sequence data, which was assembled de novo with Trinity. A transcriptome was produced after filtering and quality checking yielding a final set of 60,232 high quality transcripts for analysis. CEGMA software identified 247 out of 248 ultra-conserved core proteins as 'complete' in the transcriptome assembly, yielding a completeness of 99.6%. BLASTX and InterProScan annotated 55% of the assembled transcripts and showed that the three tissue types differed both qualitatively and quantitatively in I. elegans. Differential expression identified 8,625 transcripts to be differentially expressed in head, thorax and abdomen. Targeted analyses of vision and colour functional pathways identified the presence of four different opsin types and three pigmentation pathways. We also identified transcripts involved in temperature sensitivity, thermoregulation and olfaction. All these traits and their associated transcripts are of considerable ecological and evolutionary interest for this and other insect orders. Our work presents a comprehensive transcriptome resource for the ancient insect order Odonata and provides insight into their biology and physiology. The transcriptomic resource can provide a foundation for future investigations into this diverse group, including the evolution of colour, vision, olfaction and thermal adaptation.

Deep sequencing reveals cell-type-specific patterns of single-cell transcriptome variation.

PubMed

Dueck, Hannah; Khaladkar, Mugdha; Kim, Tae Kyung; Spaethling, Jennifer M; Francis, Chantal; Suresh, Sangita; Fisher, Stephen A; Seale, Patrick; Beck, Sheryl G; Bartfai, Tamas; Kuhn, Bernhard; Eberwine, James; Kim, Junhyong

2015-06-09

Differentiation of metazoan cells requires execution of different gene expression programs but recent single-cell transcriptome profiling has revealed considerable variation within cells of seeming identical phenotype. This brings into question the relationship between transcriptome states and cell phenotypes. Additionally, single-cell transcriptomics presents unique analysis challenges that need to be addressed to answer this question. We present high quality deep read-depth single-cell RNA sequencing for 91 cells from five mouse tissues and 18 cells from two rat tissues, along with 30 control samples of bulk RNA diluted to single-cell levels. We find that transcriptomes differ globally across tissues with regard to the number of genes expressed, the average expression patterns, and within-cell-type variation patterns. We develop methods to filter genes for reliable quantification and to calibrate biological variation. All cell types include genes with high variability in expression, in a tissue-specific manner. We also find evidence that single-cell variability of neuronal genes in mice is correlated with that in rats consistent with the hypothesis that levels of variation may be conserved. Single-cell RNA-sequencing data provide a unique view of transcriptome function; however, careful analysis is required in order to use single-cell RNA-sequencing measurements for this purpose. Technical variation must be considered in single-cell RNA-sequencing studies of expression variation. For a subset of genes, biological variability within each cell type appears to be regulated in order to perform dynamic functions, rather than solely molecular noise.

Pathway-focused bioassays and transcriptome analysis contribute to a better activity monitoring of complex herbal remedies

PubMed Central

2013-01-01

Background Transcriptome analysis in combination with pathway-focused bioassays is suggested to be a helpful approach for gaining deeper insights into the complex mechanisms of action of herbal multicomponent preparations in living cells. The polyherbalism based concept of Tibetan and Ayurvedic medicine considers therapeutic efficacy through multi-target effects. A polyherbal Indo-Tibetan preparation, Padma 28, approved by the Swiss drug authorities (Swissmedic Nr. 58436), was applied to a more detailed dissection of mechanism of action in human hepatoma HepG2 cells. Cell-free and cell-based assays were employed to evaluate the antioxidant capacity. Genome-wide expression profiling was done by applying Human Genome U133 Plus 2.0 Affymetrix arrays. Pathway- and network-oriented analysis elucidated the affected biological processes. The results were validated using reporter gene assays and quantitative real-time PCR. Results To reveal the direct radical scavenging effects of the ethanolic extract of the Indo-Tibetan polyherbal remedy Padma 28, an in vitro oxygen radical absorbance capacity assay (ORAC) was employed, which resulted in a peroxyl-radical scavenging activity of 2006 ± 235 μmol TE/g. Furthermore, the antioxidant capacity of Padma 28 was analysed in living HepG2 cells, by measuring its scavenging potential against radical induced ROS. This formulation showed a considerable antioxidant capacity by significantly reducing ROS levels in a dose-dependent manner. Integrated transcriptome analysis revealed a major influence on phase I and phase II detoxification and the oxidative stress response. Selected target genes, such as heme oxygenase 1, were validated in qPCR experiments. Network analysis showed 18 interrelated networks involved in important biological functions such as drug and bio-molecule metabolism, molecular transport and cellular communication. Some molecules are part of signaling cascades that are active during development and morphogenesis or are involved in pathological conditions and inflammatory response. Conclusions The identified molecular targets and pathways suggest several mechanisms that underlie the biological activity of the preparation. Although extrapolation of these findings to the in vivo situation is not possible, the results obtained might be the basis for further investigations and new hypotheses to be tested. This study demonstrates the potential of the combination of focused and unbiased research strategies in the mode of action analysis of multicomponent herbal mixtures. PMID:23445205

Transcriptional pathway and de novo network-based approaches to effects-based monitoring in the Great Lakes

EPA Science Inventory

Transcriptomics provides unique solutions for understanding the impact of complex mixtures and their components on aquatic systems. Here we describe the application of transcriptomics analysis of in situ fathead minnow exposures for assessing biological impacts of wastewater trea...

Transcriptome and gene expression analysis in cold-acclimated guayule (Parthenium argentatum)rubber-producing tissue

USDA-ARS?s Scientific Manuscript database

Natural rubber biosynthesis in guayule (Parthenium argentatum) is associated with moderately cold night temperatures. To begin to dissect the molecular events triggered by cold temperatures that govern rubber synthesis induction in guayule, the transcriptome of bark tissue, where rubber is produced...

Next-generation sequencing (NGS) transcriptomes reveal association of multiple genes and pathways contributing to secondary metabolites accumulation in tuberous roots of Aconitum heterophyllum Wall.

PubMed

Pal, Tarun; Malhotra, Nikhil; Chanumolu, Sree Krishna; Chauhan, Rajinder Singh

2015-07-01

The transcriptomes of Aconitum heterophyllum were assembled and characterized for the first time to decipher molecular components contributing to biosynthesis and accumulation of metabolites in tuberous roots. Aconitum heterophyllum Wall., popularly known as Atis, is a high-value medicinal herb of North-Western Himalayas. No information exists as of today on genetic factors contributing to the biosynthesis of secondary metabolites accumulating in tuberous roots, thereby, limiting genetic interventions towards genetic improvement of A. heterophyllum. Illumina paired-end sequencing followed by de novo assembly yielded 75,548 transcripts for root transcriptome and 39,100 transcripts for shoot transcriptome with minimum length of 200 bp. Biological role analysis of root versus shoot transcriptomes assigned 27,596 and 16,604 root transcripts; 12,340 and 9398 shoot transcripts into gene ontology and clusters of orthologous group, respectively. KEGG pathway mapping assigned 37 and 31 transcripts onto starch-sucrose metabolism while 329 and 341 KEGG orthologies associated with transcripts were found to be involved in biosynthesis of various secondary metabolites for root and shoot transcriptomes, respectively. In silico expression profiling of the mevalonate/2-C-methyl-D-erythritol 4-phosphate (non-mevalonate) pathway genes for aconites biosynthesis revealed 4 genes HMGR (3-hydroxy-3-methylglutaryl-CoA reductase), MVK (mevalonate kinase), MVDD (mevalonate diphosphate decarboxylase) and HDS (1-hydroxy-2-methyl-2-(E)-butenyl 4-diphosphate synthase) with higher expression in root transcriptome compared to shoot transcriptome suggesting their key role in biosynthesis of aconite alkaloids. Five genes, GMPase (geranyl diphosphate mannose pyrophosphorylase), SHAGGY, RBX1 (RING-box protein 1), SRF receptor kinases and β-amylase, implicated in tuberous root formation in other plant species showed higher levels of expression in tuberous roots compared to shoots. A total of 15,487 transcription factors belonging to bHLH, MYB, bZIP families and 399 ABC transporters which regulate biosynthesis and accumulation of bioactive compounds were identified in root and shoot transcriptomes. The expression of 5 ABC transporters involved in tuberous root development was validated by quantitative PCR analysis. Network connectivity diagrams were drawn for starch-sucrose metabolism and isoquinoline alkaloid biosynthesis associated with tuberous root growth and secondary metabolism, respectively, in root transcriptome of A. heterophyllum. The current endeavor will be of practical importance in planning a suitable genetic intervention strategy for the improvement of A. heterophyllum.

Profiling the venom gland transcriptomes of Costa Rican snakes by 454 pyrosequencing

PubMed Central

2011-01-01

Background A long term research goal of venomics, of applied importance for improving current antivenom therapy, but also for drug discovery, is to understand the pharmacological potential of venoms. Individually or combined, proteomic and transcriptomic studies have demonstrated their feasibility to explore in depth the molecular diversity of venoms. In the absence of genome sequence, transcriptomes represent also valuable searchable databases for proteomic projects. Results The venom gland transcriptomes of 8 Costa Rican taxa from 5 genera (Crotalus, Bothrops, Atropoides, Cerrophidion, and Bothriechis) of pitvipers were investigated using high-throughput 454 pyrosequencing. 100,394 out of 330,010 masked reads produced significant hits in the available databases. 5.165,220 nucleotides (8.27%) were masked by RepeatMasker, the vast majority of which corresponding to class I (retroelements) and class II (DNA transposons) mobile elements. BLAST hits included 79,991 matches to entries of the taxonomic suborder Serpentes, of which 62,433 displayed similarity to documented venom proteins. Strong discrepancies between the transcriptome-computed and the proteome-gathered toxin compositions were obvious at first sight. Although the reasons underlaying this discrepancy are elusive, since no clear trend within or between species is apparent, the data indicate that individual mRNA species may be translationally controlled in a species-dependent manner. The minimum number of genes from each toxin family transcribed into the venom gland transcriptome of each species was calculated from multiple alignments of reads matched to a full-length reference sequence of each toxin family. Reads encoding ORF regions of Kazal-type inhibitor-like proteins were uniquely found in Bothriechis schlegelii and B. lateralis transcriptomes, suggesting a genus-specific recruitment event during the early-Middle Miocene. A transcriptome-based cladogram supports the large divergence between A. mexicanus and A. picadoi, and a closer kinship between A. mexicanus and C. godmani. Conclusions Our comparative next-generation sequencing (NGS) analysis reveals taxon-specific trends governing the formulation of the venom arsenal. Knowledge of the venom proteome provides hints on the translation efficiency of toxin-coding transcripts, contributing thereby to a more accurate interpretation of the transcriptome. The application of NGS to the analysis of snake venom transcriptomes, may represent the tool for opening the door to systems venomics. PMID:21605378

A large-scale full-length cDNA analysis to explore the budding yeast transcriptome

PubMed Central

Miura, Fumihito; Kawaguchi, Noriko; Sese, Jun; Toyoda, Atsushi; Hattori, Masahira; Morishita, Shinichi; Ito, Takashi

2006-01-01

We performed a large-scale cDNA analysis to explore the transcriptome of the budding yeast Saccharomyces cerevisiae. We sequenced two cDNA libraries, one from the cells exponentially growing in a minimal medium and the other from meiotic cells. Both libraries were generated by using a vector-capping method that allows the accurate mapping of transcription start sites (TSSs). Consequently, we identified 11,575 TSSs associated with 3,638 annotated genomic features, including 3,599 ORFs, to suggest that most yeast genes have two or more TSSs. In addition, we identified 45 previously undescribed introns, including those affecting current ORF annotations and those spliced alternatively. Furthermore, the analysis revealed 667 transcription units in the intergenic regions and transcripts derived from antisense strands of 367 known features. We also found that 348 ORFs carry TSSs in their 3′-halves to generate sense transcripts starting from inside the ORFs. These results indicate that the budding yeast transcriptome is considerably more complex than previously thought, and it shares many recently revealed characteristics with the transcriptomes of mammals and other higher eukaryotes. Thus, the genome-wide active transcription that generates novel classes of transcripts appears to be an intrinsic feature of the eukaryotic cells. The budding yeast will serve as a versatile model for the studies on these aspects of transcriptome, and the full-length cDNA clones can function as an invaluable resource in such studies. PMID:17101987

Integrated genomics of Mucorales reveals novel therapeutic targets

USDA-ARS?s Scientific Manuscript database

Mucormycosis is a life-threatening infection caused by Mucorales fungi. We sequenced 30 fungal genomes and performed transcriptomics with three representative Rhizopus and Mucor strains with human airway epithelial cells during fungal invasion to reveal key host and fungal determinants contributing ...

Single-Cell RNA Sequencing of Glioblastoma Cells.

PubMed

Sen, Rajeev; Dolgalev, Igor; Bayin, N Sumru; Heguy, Adriana; Tsirigos, Aris; Placantonakis, Dimitris G

2018-01-01

Single-cell RNA sequencing (sc-RNASeq) is a recently developed technique used to evaluate the transcriptome of individual cells. As opposed to conventional RNASeq in which entire populations are sequenced in bulk, sc-RNASeq can be beneficial when trying to better understand gene expression patterns in markedly heterogeneous populations of cells or when trying to identify transcriptional signatures of rare cells that may be underrepresented when using conventional bulk RNASeq. In this method, we describe the generation and analysis of cDNA libraries from single patient-derived glioblastoma cells using the C1 Fluidigm system. The protocol details the use of the C1 integrated fluidics circuit (IFC) for capturing, imaging and lysing cells; performing reverse transcription; and generating cDNA libraries that are ready for sequencing and analysis.

Detection and Reconstruction of Circular RNAs from Transcriptomic Data.

PubMed

Zheng, Yi; Zhao, Fangqing

2018-01-01

Recent studies have shown that circular RNAs (circRNAs) are a novel class of abundant, stable, and ubiquitous noncoding RNA molecules in eukaryotic organisms. Comprehensive detection and reconstruction of circRNAs from high-throughput transcriptome data is an initial step to study their biogenesis and function. Several tools have been developed to deal with this issue, but they require many steps and are difficult to use. To solve this problem, we provide a protocol for researchers to detect and reconstruct circRNA by employing CIRI2, CIRI-AS, and CIRI-full. This protocol can not only simplify the usage of above tools but also integrate their results.

A Cross-Species Analysis in Pancreatic Neuroendocrine Tumors Reveals Molecular Subtypes with Distinctive Clinical, Metastatic, Developmental, and Metabolic Characteristics

PubMed Central

Sadanandam, Anguraj; Wullschleger, Stephan; Lyssiotis, Costas A.; Grötzinger, Carsten; Barbi, Stefano; Bersani, Samantha; Körner, Jan; Wafy, Ismael; Mafficini, Andrea; Lawlor, Rita T.; Simbolo, Michele; Asara, John M.; Bläker, Hendrik; Cantley, Lewis C.; Wiedenmann, Bertram; Scarpa, Aldo; Hanahan, Douglas

2016-01-01

Seeking to assess the representative and instructive value of an engineered mouse model of pancreatic neuroendocrine tumors (PanNET) for its cognate human cancer, we profiled and compared mRNA and miRNA transcriptomes of tumors from both. Mouse PanNET tumors could be classified into two distinctive subtypes, well-differentiated islet/insulinoma tumors (IT) and poorly differentiated tumors associated with liver metastases, dubbed metastasis-like primary (MLP). Human PanNETs were independently classified into these same two subtypes, along with a third, specific gene mutation–enriched subtype. The MLP subtypes in human and mouse were similar to liver metastases in terms of miRNA and mRNA transcriptome profiles and signature genes. The human/mouse MLP subtypes also similarly expressed genes known to regulate early pancreas development, whereas the IT subtypes expressed genes characteristic of mature islet cells, suggesting different tumorigenesis pathways. In addition, these subtypes exhibit distinct metabolic profiles marked by differential pyruvate metabolism, substantiating the significance of their separate identities. SIGNIFICANCE This study involves a comprehensive cross-species integrated analysis of multi-omics profiles and histology to stratify PanNETs into subtypes with distinctive characteristics. We provide support for the RIP1-TAG2 mouse model as representative of its cognate human cancer with prospects to better understand PanNET heterogeneity and consider future applications of personalized cancer therapy. PMID:26446169